{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# TensorFlow Classification"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data\n",
    "\n",
    "https://archive.ics.uci.edu/ml/datasets/pima+indians+diabetes\n",
    "https://www.kaggle.com/uciml/pima-indians-diabetes-database\n",
    "\n",
    "1. Title: Pima Indians Diabetes Database\n",
    "\n",
    "2. Sources:\n",
    "   (a) Original owners: National Institute of Diabetes and Digestive and\n",
    "                        Kidney Diseases\n",
    "   (b) Donor of database: Vincent Sigillito (vgs@aplcen.apl.jhu.edu)\n",
    "                          Research Center, RMI Group Leader\n",
    "                          Applied Physics Laboratory\n",
    "                          The Johns Hopkins University\n",
    "                          Johns Hopkins Road\n",
    "                          Laurel, MD 20707\n",
    "                          (301) 953-6231\n",
    "   (c) Date received: 9 May 1990\n",
    "\n",
    "3. Past Usage:\n",
    "    1. Smith,~J.~W., Everhart,~J.~E., Dickson,~W.~C., Knowler,~W.~C., \\&\n",
    "       Johannes,~R.~S. (1988). Using the ADAP learning algorithm to forecast\n",
    "       the onset of diabetes mellitus.  In {\\it Proceedings of the Symposium\n",
    "       on Computer Applications and Medical Care} (pp. 261--265).  IEEE\n",
    "       Computer Society Press.\n",
    "\n",
    "       The diagnostic, binary-valued variable investigated is whether the\n",
    "       patient shows signs of diabetes according to World Health Organization\n",
    "       criteria (i.e., if the 2 hour post-load plasma glucose was at least \n",
    "       200 mg/dl at any survey  examination or if found during routine medical\n",
    "       care).   The population lives near Phoenix, Arizona, USA.\n",
    "\n",
    "       Results: Their ADAP algorithm makes a real-valued prediction between\n",
    "       0 and 1.  This was transformed into a binary decision using a cutoff of \n",
    "       0.448.  Using 576 training instances, the sensitivity and specificity\n",
    "       of their algorithm was 76% on the remaining 192 instances.\n",
    "\n",
    "4. Relevant Information:\n",
    "      Several constraints were placed on the selection of these instances from\n",
    "      a larger database.  In particular, all patients here are females at\n",
    "      least 21 years old of Pima Indian heritage.  ADAP is an adaptive learning\n",
    "      routine that generates and executes digital analogs of perceptron-like\n",
    "      devices.  It is a unique algorithm; see the paper for details.\n",
    "\n",
    "5. Number of Instances: 768\n",
    "\n",
    "6. Number of Attributes: 8 plus class \n",
    "\n",
    "    7. For Each Attribute: (all numeric-valued)\n",
    "       1. Number of times pregnant\n",
    "       2. Plasma glucose concentration a 2 hours in an oral glucose tolerance test\n",
    "       3. Diastolic blood pressure (mm Hg)\n",
    "       4. Triceps skin fold thickness (mm)\n",
    "       5. 2-Hour serum insulin (mu U/ml)\n",
    "       6. Body mass index (weight in kg/(height in m)^2)\n",
    "       7. Diabetes pedigree function\n",
    "       8. Age (years)\n",
    "       9. Class variable (0 or 1)\n",
    "\n",
    "8. Missing Attribute Values: Yes\n",
    "\n",
    "9. Class Distribution: (class value 1 is interpreted as \"tested positive for\n",
    "   diabetes\")\n",
    "\n",
    "   Class Value  Number of instances\n",
    "   0            500\n",
    "   1            268\n",
    "\n",
    "10. Brief statistical analysis:\n",
    "\n",
    "        Attribute number:    Mean:   Standard Deviation:\n",
    "        1.                     3.8     3.4\n",
    "        2.                   120.9    32.0\n",
    "        3.                    69.1    19.4\n",
    "        4.                    20.5    16.0\n",
    "        5.                    79.8   115.2\n",
    "        6.                    32.0     7.9\n",
    "        7.                     0.5     0.3\n",
    "        8.                    33.2    11.8"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "diabetes = pd.read_csv('pima-indians-diabetes.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number_pregnant</th>\n",
       "      <th>Glucose_concentration</th>\n",
       "      <th>Blood_pressure</th>\n",
       "      <th>Triceps</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Pedigree</th>\n",
       "      <th>Age</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>0.743719</td>\n",
       "      <td>0.590164</td>\n",
       "      <td>0.353535</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500745</td>\n",
       "      <td>0.234415</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.427136</td>\n",
       "      <td>0.540984</td>\n",
       "      <td>0.292929</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.396423</td>\n",
       "      <td>0.116567</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>0.919598</td>\n",
       "      <td>0.524590</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.347243</td>\n",
       "      <td>0.253629</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>0.447236</td>\n",
       "      <td>0.540984</td>\n",
       "      <td>0.232323</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.418778</td>\n",
       "      <td>0.038002</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>0.688442</td>\n",
       "      <td>0.327869</td>\n",
       "      <td>0.353535</td>\n",
       "      <td>0.198582</td>\n",
       "      <td>0.642325</td>\n",
       "      <td>0.943638</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Number_pregnant  Glucose_concentration  Blood_pressure   Triceps   Insulin  \\\n",
       "0                6               0.743719        0.590164  0.353535  0.000000   \n",
       "1                1               0.427136        0.540984  0.292929  0.000000   \n",
       "2                8               0.919598        0.524590  0.000000  0.000000   \n",
       "3                1               0.447236        0.540984  0.232323  0.111111   \n",
       "4                0               0.688442        0.327869  0.353535  0.198582   \n",
       "\n",
       "        BMI  Pedigree  Age  Class  \n",
       "0  0.500745  0.234415   50      1  \n",
       "1  0.396423  0.116567   31      0  \n",
       "2  0.347243  0.253629   32      1  \n",
       "3  0.418778  0.038002   21      0  \n",
       "4  0.642325  0.943638   33      1  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diabetes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Number_pregnant', 'Glucose_concentration', 'Blood_pressure', 'Triceps',\n",
       "       'Insulin', 'BMI', 'Pedigree', 'Age', 'Class'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diabetes.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean the Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "cols_to_norm = ['Number_pregnant', 'Glucose_concentration', 'Blood_pressure', 'Triceps',\n",
    "       'Insulin', 'BMI', 'Pedigree']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Normalize**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "diabetes[cols_to_norm] = diabetes[cols_to_norm].apply(lambda x: (x - x.min()) / (x.max() - x.min()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number_pregnant</th>\n",
       "      <th>Glucose_concentration</th>\n",
       "      <th>Blood_pressure</th>\n",
       "      <th>Triceps</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Pedigree</th>\n",
       "      <th>Age</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.352941</td>\n",
       "      <td>0.743719</td>\n",
       "      <td>0.590164</td>\n",
       "      <td>0.353535</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500745</td>\n",
       "      <td>0.234415</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.058824</td>\n",
       "      <td>0.427136</td>\n",
       "      <td>0.540984</td>\n",
       "      <td>0.292929</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.396423</td>\n",
       "      <td>0.116567</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.470588</td>\n",
       "      <td>0.919598</td>\n",
       "      <td>0.524590</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.347243</td>\n",
       "      <td>0.253629</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.058824</td>\n",
       "      <td>0.447236</td>\n",
       "      <td>0.540984</td>\n",
       "      <td>0.232323</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.418778</td>\n",
       "      <td>0.038002</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.688442</td>\n",
       "      <td>0.327869</td>\n",
       "      <td>0.353535</td>\n",
       "      <td>0.198582</td>\n",
       "      <td>0.642325</td>\n",
       "      <td>0.943638</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Number_pregnant  Glucose_concentration  Blood_pressure   Triceps   Insulin  \\\n",
       "0         0.352941               0.743719        0.590164  0.353535  0.000000   \n",
       "1         0.058824               0.427136        0.540984  0.292929  0.000000   \n",
       "2         0.470588               0.919598        0.524590  0.000000  0.000000   \n",
       "3         0.058824               0.447236        0.540984  0.232323  0.111111   \n",
       "4         0.000000               0.688442        0.327869  0.353535  0.198582   \n",
       "\n",
       "        BMI  Pedigree  Age  Class  \n",
       "0  0.500745  0.234415   50      1  \n",
       "1  0.396423  0.116567   31      0  \n",
       "2  0.347243  0.253629   32      1  \n",
       "3  0.418778  0.038002   21      0  \n",
       "4  0.642325  0.943638   33      1  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diabetes.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Feature Columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Number_pregnant', 'Glucose_concentration', 'Blood_pressure', 'Triceps',\n",
       "       'Insulin', 'BMI', 'Pedigree', 'Age', 'Class'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diabetes.columns "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Continuous Features\n",
    "\n",
    "* Number of times pregnant\n",
    "* Plasma glucose concentration a 2 hours in an oral glucose tolerance test\n",
    "* Diastolic blood pressure (mm Hg)\n",
    "* Triceps skin fold thickness (mm)\n",
    "* 2-Hour serum insulin (mu U/ml)\n",
    "* Body mass index (weight in kg/(height in m)^2)\n",
    "* Diabetes pedigree function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Encode Age to Age Groups"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x11f2a5978>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "diabetes['Age'].hist(bins=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "bins = [0,30,50,70,100]\n",
    "labels =[0,1,2,3]\n",
    "diabetes[\"Age_buckets\"] = pd.cut(diabetes[\"Age\"],bins=bins, labels=labels, include_lowest=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Putting them together"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train Test Split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Number_pregnant</th>\n",
       "      <th>Glucose_concentration</th>\n",
       "      <th>Blood_pressure</th>\n",
       "      <th>Triceps</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>Pedigree</th>\n",
       "      <th>Age</th>\n",
       "      <th>Class</th>\n",
       "      <th>Age_buckets</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.352941</td>\n",
       "      <td>0.743719</td>\n",
       "      <td>0.590164</td>\n",
       "      <td>0.353535</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.500745</td>\n",
       "      <td>0.234415</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.058824</td>\n",
       "      <td>0.427136</td>\n",
       "      <td>0.540984</td>\n",
       "      <td>0.292929</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.396423</td>\n",
       "      <td>0.116567</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.470588</td>\n",
       "      <td>0.919598</td>\n",
       "      <td>0.524590</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.347243</td>\n",
       "      <td>0.253629</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.058824</td>\n",
       "      <td>0.447236</td>\n",
       "      <td>0.540984</td>\n",
       "      <td>0.232323</td>\n",
       "      <td>0.111111</td>\n",
       "      <td>0.418778</td>\n",
       "      <td>0.038002</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.688442</td>\n",
       "      <td>0.327869</td>\n",
       "      <td>0.353535</td>\n",
       "      <td>0.198582</td>\n",
       "      <td>0.642325</td>\n",
       "      <td>0.943638</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Number_pregnant  Glucose_concentration  Blood_pressure   Triceps   Insulin  \\\n",
       "0         0.352941               0.743719        0.590164  0.353535  0.000000   \n",
       "1         0.058824               0.427136        0.540984  0.292929  0.000000   \n",
       "2         0.470588               0.919598        0.524590  0.000000  0.000000   \n",
       "3         0.058824               0.447236        0.540984  0.232323  0.111111   \n",
       "4         0.000000               0.688442        0.327869  0.353535  0.198582   \n",
       "\n",
       "        BMI  Pedigree  Age  Class Age_buckets  \n",
       "0  0.500745  0.234415   50      1           1  \n",
       "1  0.396423  0.116567   31      0           1  \n",
       "2  0.347243  0.253629   32      1           1  \n",
       "3  0.418778  0.038002   21      0           0  \n",
       "4  0.642325  0.943638   33      1           1  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "diabetes.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 10 columns):\n",
      "Number_pregnant          768 non-null float64\n",
      "Glucose_concentration    768 non-null float64\n",
      "Blood_pressure           768 non-null float64\n",
      "Triceps                  768 non-null float64\n",
      "Insulin                  768 non-null float64\n",
      "BMI                      768 non-null float64\n",
      "Pedigree                 768 non-null float64\n",
      "Age                      768 non-null int64\n",
      "Class                    768 non-null int64\n",
      "Age_buckets              768 non-null category\n",
      "dtypes: category(1), float64(7), int64(2)\n",
      "memory usage: 55.0 KB\n"
     ]
    }
   ],
   "source": [
    "diabetes.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_data = diabetes.drop(['Age','Class'],axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "labels = diabetes['Class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = train_test_split(x_data,labels,test_size=0.33, random_state=101)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(514,)"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense,Activation\n",
    "from tensorflow.keras.optimizers import SGD,Adam\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "from tensorflow import keras"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "dense_19 (Dense)             (None, 20)                180       \n",
      "_________________________________________________________________\n",
      "dropout_7 (Dropout)          (None, 20)                0         \n",
      "_________________________________________________________________\n",
      "dense_20 (Dense)             (None, 20)                420       \n",
      "_________________________________________________________________\n",
      "dropout_8 (Dropout)          (None, 20)                0         \n",
      "_________________________________________________________________\n",
      "dense_21 (Dense)             (None, 10)                210       \n",
      "_________________________________________________________________\n",
      "dropout_9 (Dropout)          (None, 10)                0         \n",
      "_________________________________________________________________\n",
      "dense_22 (Dense)             (None, 2)                 22        \n",
      "=================================================================\n",
      "Total params: 832\n",
      "Trainable params: 832\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = Sequential()\n",
    "#model.add(Dense(2,input_shape = (X_train.shape[1],),activation = 'softmax'))\n",
    "model.add(Dense(20,input_shape = (X_train.shape[1],),\n",
    "                activation = 'relu', \n",
    "                kernel_regularizer = keras.regularizers.l2(0.001)))\n",
    "model.add(keras.layers.Dropout(0.5))\n",
    "model.add(Dense(20,input_shape = (X_train.shape[1],),\n",
    "                activation = 'relu', \n",
    "                kernel_regularizer = keras.regularizers.l2(0.001)))\n",
    "model.add(keras.layers.Dropout(0.5))\n",
    "model.add(Dense(10,activation = 'relu',\n",
    "               kernel_regularizer = keras.regularizers.l2(0.001)))\n",
    "model.add(keras.layers.Dropout(0.5))\n",
    "#model.add(Dense(10,activation = 'relu'))\n",
    "model.add(Dense(2, activation = 'softmax'))\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "adam = Adam(0.001)\n",
    "#sgd = SGD(0.005)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_binary_train= to_categorical(y_train)\n",
    "y_binary_test = to_categorical(y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(loss = 'categorical_crossentropy', optimizer = adam, metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 514 samples, validate on 254 samples\n",
      "Epoch 1/2000\n",
      "514/514 [==============================] - 2s 5ms/step - loss: 0.7468 - acc: 0.5156 - val_loss: 0.7323 - val_acc: 0.5787\n",
      "Epoch 2/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.7565 - acc: 0.5428 - val_loss: 0.7205 - val_acc: 0.6299\n",
      "Epoch 3/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.7369 - acc: 0.5778 - val_loss: 0.7129 - val_acc: 0.6378\n",
      "Epoch 4/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.7270 - acc: 0.6187 - val_loss: 0.7065 - val_acc: 0.6575\n",
      "Epoch 5/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.7074 - acc: 0.6459 - val_loss: 0.7008 - val_acc: 0.6575\n",
      "Epoch 6/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.7141 - acc: 0.6304 - val_loss: 0.6974 - val_acc: 0.6575\n",
      "Epoch 7/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.7037 - acc: 0.6401 - val_loss: 0.6939 - val_acc: 0.6575\n",
      "Epoch 8/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.7041 - acc: 0.6401 - val_loss: 0.6912 - val_acc: 0.6575\n",
      "Epoch 9/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.6952 - acc: 0.6595 - val_loss: 0.6889 - val_acc: 0.6575\n",
      "Epoch 10/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.6880 - acc: 0.6576 - val_loss: 0.6856 - val_acc: 0.6575\n",
      "Epoch 11/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.7099 - acc: 0.6304 - val_loss: 0.6826 - val_acc: 0.6575\n",
      "Epoch 12/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.6916 - acc: 0.6459 - val_loss: 0.6811 - val_acc: 0.6575\n",
      "Epoch 13/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.6887 - acc: 0.6440 - val_loss: 0.6795 - val_acc: 0.6575\n",
      "Epoch 14/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.6885 - acc: 0.6537 - val_loss: 0.6783 - val_acc: 0.6575\n",
      "Epoch 15/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.6859 - acc: 0.6518 - val_loss: 0.6761 - val_acc: 0.6575\n",
      "Epoch 16/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.6755 - acc: 0.6595 - val_loss: 0.6735 - val_acc: 0.6575\n",
      "Epoch 17/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.6843 - acc: 0.6537 - val_loss: 0.6718 - val_acc: 0.6575\n",
      "Epoch 18/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.6782 - acc: 0.6440 - val_loss: 0.6713 - val_acc: 0.6575\n",
      "Epoch 19/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.6808 - acc: 0.6401 - val_loss: 0.6702 - val_acc: 0.6575\n",
      "Epoch 20/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.6754 - acc: 0.6498 - val_loss: 0.6693 - val_acc: 0.6575\n",
      "Epoch 21/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.6669 - acc: 0.6537 - val_loss: 0.6681 - val_acc: 0.6575\n",
      "Epoch 22/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.6778 - acc: 0.6498 - val_loss: 0.6669 - val_acc: 0.6575\n",
      "Epoch 23/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.6736 - acc: 0.6420 - val_loss: 0.6653 - val_acc: 0.6575\n",
      "Epoch 24/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.6714 - acc: 0.6537 - val_loss: 0.6636 - val_acc: 0.6575\n",
      "Epoch 25/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.6630 - acc: 0.6420 - val_loss: 0.6607 - val_acc: 0.6575\n",
      "Epoch 26/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.6778 - acc: 0.6401 - val_loss: 0.6591 - val_acc: 0.6575\n",
      "Epoch 27/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.6650 - acc: 0.6498 - val_loss: 0.6578 - val_acc: 0.6575\n",
      "Epoch 28/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.6630 - acc: 0.6440 - val_loss: 0.6559 - val_acc: 0.6575\n",
      "Epoch 29/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.6712 - acc: 0.6420 - val_loss: 0.6562 - val_acc: 0.6575\n",
      "Epoch 30/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.6568 - acc: 0.6518 - val_loss: 0.6550 - val_acc: 0.6575\n",
      "Epoch 31/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.6606 - acc: 0.6401 - val_loss: 0.6532 - val_acc: 0.6575\n",
      "Epoch 32/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.6621 - acc: 0.6498 - val_loss: 0.6515 - val_acc: 0.6575\n",
      "Epoch 33/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.6755 - acc: 0.6401 - val_loss: 0.6517 - val_acc: 0.6575\n",
      "Epoch 34/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.6602 - acc: 0.6440 - val_loss: 0.6510 - val_acc: 0.6575\n",
      "Epoch 35/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.6567 - acc: 0.6479 - val_loss: 0.6496 - val_acc: 0.6575\n",
      "Epoch 36/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.6591 - acc: 0.6459 - val_loss: 0.6491 - val_acc: 0.6575\n",
      "Epoch 37/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.6575 - acc: 0.6479 - val_loss: 0.6488 - val_acc: 0.6575\n",
      "Epoch 38/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6559 - acc: 0.6537 - val_loss: 0.6484 - val_acc: 0.6575\n",
      "Epoch 39/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.6635 - acc: 0.6459 - val_loss: 0.6465 - val_acc: 0.6575\n",
      "Epoch 40/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.6548 - acc: 0.6498 - val_loss: 0.6460 - val_acc: 0.6575\n",
      "Epoch 41/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.6534 - acc: 0.6556 - val_loss: 0.6443 - val_acc: 0.6575\n",
      "Epoch 42/2000\n",
      "514/514 [==============================] - 0s 174us/step - loss: 0.6561 - acc: 0.6498 - val_loss: 0.6429 - val_acc: 0.6575\n",
      "Epoch 43/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.6476 - acc: 0.6479 - val_loss: 0.6409 - val_acc: 0.6575\n",
      "Epoch 44/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.6568 - acc: 0.6440 - val_loss: 0.6404 - val_acc: 0.6575\n",
      "Epoch 45/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.6495 - acc: 0.6479 - val_loss: 0.6385 - val_acc: 0.6575\n",
      "Epoch 46/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6519 - acc: 0.6459 - val_loss: 0.6368 - val_acc: 0.6575\n",
      "Epoch 47/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6526 - acc: 0.6498 - val_loss: 0.6336 - val_acc: 0.6575\n",
      "Epoch 48/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.6478 - acc: 0.6518 - val_loss: 0.6324 - val_acc: 0.6575\n",
      "Epoch 49/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.6418 - acc: 0.6537 - val_loss: 0.6305 - val_acc: 0.6575\n",
      "Epoch 50/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.6416 - acc: 0.6440 - val_loss: 0.6288 - val_acc: 0.6575\n",
      "Epoch 51/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.6469 - acc: 0.6479 - val_loss: 0.6267 - val_acc: 0.6575\n",
      "Epoch 52/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.6324 - acc: 0.6595 - val_loss: 0.6250 - val_acc: 0.6575\n",
      "Epoch 53/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.6380 - acc: 0.6537 - val_loss: 0.6241 - val_acc: 0.6575\n",
      "Epoch 54/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.6486 - acc: 0.6420 - val_loss: 0.6231 - val_acc: 0.6575\n",
      "Epoch 55/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.6486 - acc: 0.6576 - val_loss: 0.6232 - val_acc: 0.6575\n",
      "Epoch 56/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.6282 - acc: 0.6576 - val_loss: 0.6213 - val_acc: 0.6575\n",
      "Epoch 57/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.6442 - acc: 0.6479 - val_loss: 0.6194 - val_acc: 0.6575\n",
      "Epoch 58/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.6355 - acc: 0.6401 - val_loss: 0.6151 - val_acc: 0.6575\n",
      "Epoch 59/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.6319 - acc: 0.6693 - val_loss: 0.6138 - val_acc: 0.6575\n",
      "Epoch 60/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 187us/step - loss: 0.6343 - acc: 0.6518 - val_loss: 0.6140 - val_acc: 0.6575\n",
      "Epoch 61/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.6312 - acc: 0.6712 - val_loss: 0.6122 - val_acc: 0.6575\n",
      "Epoch 62/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.6180 - acc: 0.6829 - val_loss: 0.6091 - val_acc: 0.6575\n",
      "Epoch 63/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.6312 - acc: 0.6732 - val_loss: 0.6075 - val_acc: 0.6575\n",
      "Epoch 64/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.6223 - acc: 0.6809 - val_loss: 0.6049 - val_acc: 0.6575\n",
      "Epoch 65/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6149 - acc: 0.6790 - val_loss: 0.6024 - val_acc: 0.6535\n",
      "Epoch 66/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.6186 - acc: 0.6770 - val_loss: 0.6047 - val_acc: 0.6575\n",
      "Epoch 67/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.6208 - acc: 0.6595 - val_loss: 0.6039 - val_acc: 0.6575\n",
      "Epoch 68/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6265 - acc: 0.6537 - val_loss: 0.6041 - val_acc: 0.6575\n",
      "Epoch 69/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.6168 - acc: 0.6732 - val_loss: 0.5983 - val_acc: 0.6535\n",
      "Epoch 70/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.6185 - acc: 0.6673 - val_loss: 0.5968 - val_acc: 0.6535\n",
      "Epoch 71/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.6084 - acc: 0.6809 - val_loss: 0.5944 - val_acc: 0.6575\n",
      "Epoch 72/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.6053 - acc: 0.6887 - val_loss: 0.5914 - val_acc: 0.6575\n",
      "Epoch 73/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6152 - acc: 0.6693 - val_loss: 0.5915 - val_acc: 0.6535\n",
      "Epoch 74/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.6086 - acc: 0.6809 - val_loss: 0.5881 - val_acc: 0.6575\n",
      "Epoch 75/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.6254 - acc: 0.6401 - val_loss: 0.5871 - val_acc: 0.6575\n",
      "Epoch 76/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.6146 - acc: 0.6673 - val_loss: 0.5874 - val_acc: 0.6575\n",
      "Epoch 77/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.6052 - acc: 0.6790 - val_loss: 0.5879 - val_acc: 0.6535\n",
      "Epoch 78/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.6212 - acc: 0.6673 - val_loss: 0.5869 - val_acc: 0.6535\n",
      "Epoch 79/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5999 - acc: 0.6848 - val_loss: 0.5847 - val_acc: 0.6535\n",
      "Epoch 80/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6149 - acc: 0.6809 - val_loss: 0.5806 - val_acc: 0.6575\n",
      "Epoch 81/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.6162 - acc: 0.6479 - val_loss: 0.5842 - val_acc: 0.6535\n",
      "Epoch 82/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.6014 - acc: 0.6732 - val_loss: 0.5829 - val_acc: 0.6535\n",
      "Epoch 83/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.6022 - acc: 0.6848 - val_loss: 0.5761 - val_acc: 0.6654\n",
      "Epoch 84/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.6086 - acc: 0.6848 - val_loss: 0.5750 - val_acc: 0.6693\n",
      "Epoch 85/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5921 - acc: 0.7004 - val_loss: 0.5703 - val_acc: 0.6811\n",
      "Epoch 86/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.6061 - acc: 0.6712 - val_loss: 0.5672 - val_acc: 0.7244\n",
      "Epoch 87/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5803 - acc: 0.7121 - val_loss: 0.5647 - val_acc: 0.7283\n",
      "Epoch 88/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5919 - acc: 0.6770 - val_loss: 0.5661 - val_acc: 0.7008\n",
      "Epoch 89/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5923 - acc: 0.7043 - val_loss: 0.5660 - val_acc: 0.7283\n",
      "Epoch 90/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5811 - acc: 0.7121 - val_loss: 0.5627 - val_acc: 0.6850\n",
      "Epoch 91/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5952 - acc: 0.6829 - val_loss: 0.5646 - val_acc: 0.6772\n",
      "Epoch 92/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5956 - acc: 0.6770 - val_loss: 0.5607 - val_acc: 0.6969\n",
      "Epoch 93/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5880 - acc: 0.6829 - val_loss: 0.5577 - val_acc: 0.7323\n",
      "Epoch 94/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5960 - acc: 0.6712 - val_loss: 0.5571 - val_acc: 0.7165\n",
      "Epoch 95/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5997 - acc: 0.6770 - val_loss: 0.5589 - val_acc: 0.7362\n",
      "Epoch 96/2000\n",
      "514/514 [==============================] - 0s 223us/step - loss: 0.5818 - acc: 0.6907 - val_loss: 0.5562 - val_acc: 0.7559\n",
      "Epoch 97/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5976 - acc: 0.6809 - val_loss: 0.5517 - val_acc: 0.7598\n",
      "Epoch 98/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5703 - acc: 0.7121 - val_loss: 0.5470 - val_acc: 0.7559\n",
      "Epoch 99/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5996 - acc: 0.7043 - val_loss: 0.5480 - val_acc: 0.7559\n",
      "Epoch 100/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5893 - acc: 0.7023 - val_loss: 0.5488 - val_acc: 0.7598\n",
      "Epoch 101/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5809 - acc: 0.7004 - val_loss: 0.5459 - val_acc: 0.7598\n",
      "Epoch 102/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5654 - acc: 0.7276 - val_loss: 0.5423 - val_acc: 0.7638\n",
      "Epoch 103/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5871 - acc: 0.7140 - val_loss: 0.5379 - val_acc: 0.7598\n",
      "Epoch 104/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.6061 - acc: 0.7043 - val_loss: 0.5448 - val_acc: 0.7598\n",
      "Epoch 105/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5819 - acc: 0.6809 - val_loss: 0.5451 - val_acc: 0.7559\n",
      "Epoch 106/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5697 - acc: 0.7043 - val_loss: 0.5431 - val_acc: 0.7598\n",
      "Epoch 107/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5993 - acc: 0.6887 - val_loss: 0.5414 - val_acc: 0.7559\n",
      "Epoch 108/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5747 - acc: 0.6829 - val_loss: 0.5383 - val_acc: 0.7638\n",
      "Epoch 109/2000\n",
      "514/514 [==============================] - 0s 174us/step - loss: 0.5789 - acc: 0.6829 - val_loss: 0.5354 - val_acc: 0.7638\n",
      "Epoch 110/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5849 - acc: 0.6907 - val_loss: 0.5369 - val_acc: 0.7677\n",
      "Epoch 111/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5749 - acc: 0.7140 - val_loss: 0.5383 - val_acc: 0.7677\n",
      "Epoch 112/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5744 - acc: 0.7101 - val_loss: 0.5363 - val_acc: 0.7598\n",
      "Epoch 113/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5788 - acc: 0.6868 - val_loss: 0.5310 - val_acc: 0.7756\n",
      "Epoch 114/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5703 - acc: 0.7082 - val_loss: 0.5272 - val_acc: 0.7638\n",
      "Epoch 115/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5672 - acc: 0.7101 - val_loss: 0.5265 - val_acc: 0.7638\n",
      "Epoch 116/2000\n",
      "514/514 [==============================] - 0s 172us/step - loss: 0.5618 - acc: 0.7160 - val_loss: 0.5247 - val_acc: 0.7717\n",
      "Epoch 117/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5806 - acc: 0.7198 - val_loss: 0.5226 - val_acc: 0.7638\n",
      "Epoch 118/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5697 - acc: 0.7218 - val_loss: 0.5228 - val_acc: 0.7598\n",
      "Epoch 119/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5634 - acc: 0.7315 - val_loss: 0.5203 - val_acc: 0.7795\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 120/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5661 - acc: 0.7218 - val_loss: 0.5218 - val_acc: 0.7756\n",
      "Epoch 121/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5624 - acc: 0.7257 - val_loss: 0.5222 - val_acc: 0.7795\n",
      "Epoch 122/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5579 - acc: 0.7082 - val_loss: 0.5213 - val_acc: 0.7795\n",
      "Epoch 123/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5561 - acc: 0.7140 - val_loss: 0.5214 - val_acc: 0.7756\n",
      "Epoch 124/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5627 - acc: 0.7179 - val_loss: 0.5307 - val_acc: 0.7677\n",
      "Epoch 125/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5551 - acc: 0.7062 - val_loss: 0.5255 - val_acc: 0.7756\n",
      "Epoch 126/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5605 - acc: 0.7218 - val_loss: 0.5239 - val_acc: 0.7717\n",
      "Epoch 127/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5687 - acc: 0.7121 - val_loss: 0.5237 - val_acc: 0.7795\n",
      "Epoch 128/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5563 - acc: 0.7237 - val_loss: 0.5213 - val_acc: 0.7717\n",
      "Epoch 129/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5510 - acc: 0.7257 - val_loss: 0.5176 - val_acc: 0.7717\n",
      "Epoch 130/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5587 - acc: 0.7160 - val_loss: 0.5137 - val_acc: 0.7795\n",
      "Epoch 131/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5648 - acc: 0.7023 - val_loss: 0.5120 - val_acc: 0.7795\n",
      "Epoch 132/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5750 - acc: 0.7296 - val_loss: 0.5147 - val_acc: 0.7756\n",
      "Epoch 133/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5665 - acc: 0.7062 - val_loss: 0.5135 - val_acc: 0.7756\n",
      "Epoch 134/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5593 - acc: 0.7315 - val_loss: 0.5140 - val_acc: 0.7874\n",
      "Epoch 135/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5531 - acc: 0.7335 - val_loss: 0.5156 - val_acc: 0.7795\n",
      "Epoch 136/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5487 - acc: 0.7160 - val_loss: 0.5108 - val_acc: 0.7795\n",
      "Epoch 137/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5477 - acc: 0.7296 - val_loss: 0.5094 - val_acc: 0.7913\n",
      "Epoch 138/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5650 - acc: 0.7257 - val_loss: 0.5094 - val_acc: 0.7835\n",
      "Epoch 139/2000\n",
      "514/514 [==============================] - 0s 173us/step - loss: 0.5546 - acc: 0.7062 - val_loss: 0.5076 - val_acc: 0.7835\n",
      "Epoch 140/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5439 - acc: 0.7393 - val_loss: 0.5072 - val_acc: 0.7480\n",
      "Epoch 141/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5522 - acc: 0.7140 - val_loss: 0.5066 - val_acc: 0.7795\n",
      "Epoch 142/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5425 - acc: 0.7140 - val_loss: 0.5114 - val_acc: 0.7874\n",
      "Epoch 143/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5502 - acc: 0.7218 - val_loss: 0.5101 - val_acc: 0.7835\n",
      "Epoch 144/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5349 - acc: 0.7412 - val_loss: 0.5058 - val_acc: 0.7874\n",
      "Epoch 145/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5322 - acc: 0.7549 - val_loss: 0.5050 - val_acc: 0.7835\n",
      "Epoch 146/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5770 - acc: 0.7043 - val_loss: 0.5049 - val_acc: 0.7756\n",
      "Epoch 147/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5542 - acc: 0.7198 - val_loss: 0.5053 - val_acc: 0.7756\n",
      "Epoch 148/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5468 - acc: 0.7412 - val_loss: 0.5066 - val_acc: 0.7756\n",
      "Epoch 149/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5580 - acc: 0.7218 - val_loss: 0.5054 - val_acc: 0.7835\n",
      "Epoch 150/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5375 - acc: 0.7218 - val_loss: 0.5042 - val_acc: 0.7874\n",
      "Epoch 151/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5241 - acc: 0.7568 - val_loss: 0.5031 - val_acc: 0.7677\n",
      "Epoch 152/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5325 - acc: 0.7568 - val_loss: 0.5031 - val_acc: 0.7717\n",
      "Epoch 153/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5419 - acc: 0.7257 - val_loss: 0.5024 - val_acc: 0.7717\n",
      "Epoch 154/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5384 - acc: 0.7354 - val_loss: 0.5022 - val_acc: 0.7874\n",
      "Epoch 155/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5521 - acc: 0.7335 - val_loss: 0.5021 - val_acc: 0.7835\n",
      "Epoch 156/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5247 - acc: 0.7412 - val_loss: 0.5016 - val_acc: 0.7953\n",
      "Epoch 157/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5720 - acc: 0.7198 - val_loss: 0.5029 - val_acc: 0.7874\n",
      "Epoch 158/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5577 - acc: 0.7198 - val_loss: 0.5032 - val_acc: 0.7835\n",
      "Epoch 159/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5612 - acc: 0.7296 - val_loss: 0.5029 - val_acc: 0.7953\n",
      "Epoch 160/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5568 - acc: 0.7179 - val_loss: 0.5031 - val_acc: 0.7913\n",
      "Epoch 161/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5405 - acc: 0.7393 - val_loss: 0.5035 - val_acc: 0.7874\n",
      "Epoch 162/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5655 - acc: 0.6984 - val_loss: 0.5044 - val_acc: 0.7795\n",
      "Epoch 163/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5325 - acc: 0.7335 - val_loss: 0.5055 - val_acc: 0.7874\n",
      "Epoch 164/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5505 - acc: 0.7412 - val_loss: 0.5086 - val_acc: 0.7874\n",
      "Epoch 165/2000\n",
      "514/514 [==============================] - 0s 167us/step - loss: 0.5564 - acc: 0.7160 - val_loss: 0.5062 - val_acc: 0.7953\n",
      "Epoch 166/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5527 - acc: 0.7315 - val_loss: 0.5042 - val_acc: 0.7913\n",
      "Epoch 167/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5463 - acc: 0.7412 - val_loss: 0.5004 - val_acc: 0.7953\n",
      "Epoch 168/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5273 - acc: 0.7451 - val_loss: 0.5012 - val_acc: 0.7717\n",
      "Epoch 169/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5762 - acc: 0.7237 - val_loss: 0.5083 - val_acc: 0.7441\n",
      "Epoch 170/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5479 - acc: 0.7471 - val_loss: 0.5032 - val_acc: 0.7992\n",
      "Epoch 171/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5192 - acc: 0.7724 - val_loss: 0.5017 - val_acc: 0.7874\n",
      "Epoch 172/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5477 - acc: 0.7432 - val_loss: 0.5018 - val_acc: 0.7953\n",
      "Epoch 173/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5365 - acc: 0.7315 - val_loss: 0.5008 - val_acc: 0.7913\n",
      "Epoch 174/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5551 - acc: 0.7101 - val_loss: 0.5113 - val_acc: 0.7441\n",
      "Epoch 175/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5564 - acc: 0.7121 - val_loss: 0.5057 - val_acc: 0.7795\n",
      "Epoch 176/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5205 - acc: 0.7296 - val_loss: 0.5002 - val_acc: 0.7953\n",
      "Epoch 177/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5289 - acc: 0.7335 - val_loss: 0.4997 - val_acc: 0.8031\n",
      "Epoch 178/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5378 - acc: 0.7646 - val_loss: 0.5021 - val_acc: 0.7677\n",
      "Epoch 179/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 183us/step - loss: 0.5435 - acc: 0.7276 - val_loss: 0.5021 - val_acc: 0.7677\n",
      "Epoch 180/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5568 - acc: 0.7374 - val_loss: 0.4983 - val_acc: 0.7835\n",
      "Epoch 181/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5424 - acc: 0.7354 - val_loss: 0.4972 - val_acc: 0.7913\n",
      "Epoch 182/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5485 - acc: 0.7160 - val_loss: 0.4974 - val_acc: 0.7874\n",
      "Epoch 183/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5291 - acc: 0.7510 - val_loss: 0.4978 - val_acc: 0.7874\n",
      "Epoch 184/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5142 - acc: 0.7665 - val_loss: 0.4989 - val_acc: 0.7598\n",
      "Epoch 185/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5478 - acc: 0.7471 - val_loss: 0.4967 - val_acc: 0.7717\n",
      "Epoch 186/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5423 - acc: 0.7335 - val_loss: 0.4953 - val_acc: 0.7992\n",
      "Epoch 187/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5377 - acc: 0.7529 - val_loss: 0.4973 - val_acc: 0.7717\n",
      "Epoch 188/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5151 - acc: 0.7607 - val_loss: 0.4949 - val_acc: 0.7756\n",
      "Epoch 189/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5269 - acc: 0.7354 - val_loss: 0.4945 - val_acc: 0.7953\n",
      "Epoch 190/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5493 - acc: 0.7237 - val_loss: 0.4960 - val_acc: 0.7795\n",
      "Epoch 191/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5213 - acc: 0.7471 - val_loss: 0.4949 - val_acc: 0.7913\n",
      "Epoch 192/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5506 - acc: 0.7140 - val_loss: 0.4953 - val_acc: 0.7913\n",
      "Epoch 193/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5492 - acc: 0.7335 - val_loss: 0.4960 - val_acc: 0.7795\n",
      "Epoch 194/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5654 - acc: 0.7237 - val_loss: 0.4962 - val_acc: 0.7913\n",
      "Epoch 195/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5408 - acc: 0.7335 - val_loss: 0.4965 - val_acc: 0.7835\n",
      "Epoch 196/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5471 - acc: 0.7432 - val_loss: 0.4962 - val_acc: 0.7795\n",
      "Epoch 197/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5391 - acc: 0.7782 - val_loss: 0.4967 - val_acc: 0.7677\n",
      "Epoch 198/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5255 - acc: 0.7451 - val_loss: 0.4952 - val_acc: 0.7795\n",
      "Epoch 199/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.5425 - acc: 0.7335 - val_loss: 0.4945 - val_acc: 0.7913\n",
      "Epoch 200/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5303 - acc: 0.7529 - val_loss: 0.4967 - val_acc: 0.7756\n",
      "Epoch 201/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5453 - acc: 0.7257 - val_loss: 0.4983 - val_acc: 0.7756\n",
      "Epoch 202/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5326 - acc: 0.7490 - val_loss: 0.4964 - val_acc: 0.7913\n",
      "Epoch 203/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5201 - acc: 0.7315 - val_loss: 0.4937 - val_acc: 0.8031\n",
      "Epoch 204/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5498 - acc: 0.7529 - val_loss: 0.4955 - val_acc: 0.7913\n",
      "Epoch 205/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5642 - acc: 0.7432 - val_loss: 0.4977 - val_acc: 0.7835\n",
      "Epoch 206/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5222 - acc: 0.7374 - val_loss: 0.4951 - val_acc: 0.7992\n",
      "Epoch 207/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5396 - acc: 0.7354 - val_loss: 0.4952 - val_acc: 0.7913\n",
      "Epoch 208/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5321 - acc: 0.7335 - val_loss: 0.5024 - val_acc: 0.7717\n",
      "Epoch 209/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5211 - acc: 0.7588 - val_loss: 0.4924 - val_acc: 0.7953\n",
      "Epoch 210/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5086 - acc: 0.7451 - val_loss: 0.4925 - val_acc: 0.7795\n",
      "Epoch 211/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5372 - acc: 0.7257 - val_loss: 0.4923 - val_acc: 0.7913\n",
      "Epoch 212/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5257 - acc: 0.7879 - val_loss: 0.4947 - val_acc: 0.7756\n",
      "Epoch 213/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5413 - acc: 0.7549 - val_loss: 0.4969 - val_acc: 0.7756\n",
      "Epoch 214/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5461 - acc: 0.7315 - val_loss: 0.4959 - val_acc: 0.7717\n",
      "Epoch 215/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5399 - acc: 0.7335 - val_loss: 0.4951 - val_acc: 0.7756\n",
      "Epoch 216/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5602 - acc: 0.7257 - val_loss: 0.4939 - val_acc: 0.7874\n",
      "Epoch 217/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5294 - acc: 0.7529 - val_loss: 0.4946 - val_acc: 0.7795\n",
      "Epoch 218/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5523 - acc: 0.7198 - val_loss: 0.4952 - val_acc: 0.7638\n",
      "Epoch 219/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5437 - acc: 0.7160 - val_loss: 0.4936 - val_acc: 0.7913\n",
      "Epoch 220/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5295 - acc: 0.7374 - val_loss: 0.4939 - val_acc: 0.7874\n",
      "Epoch 221/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5182 - acc: 0.7626 - val_loss: 0.4961 - val_acc: 0.7677\n",
      "Epoch 222/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5273 - acc: 0.7393 - val_loss: 0.4948 - val_acc: 0.7835\n",
      "Epoch 223/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5333 - acc: 0.7393 - val_loss: 0.4932 - val_acc: 0.7795\n",
      "Epoch 224/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5474 - acc: 0.7374 - val_loss: 0.4926 - val_acc: 0.7756\n",
      "Epoch 225/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5153 - acc: 0.7471 - val_loss: 0.4915 - val_acc: 0.7795\n",
      "Epoch 226/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5316 - acc: 0.7490 - val_loss: 0.4913 - val_acc: 0.7795\n",
      "Epoch 227/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5339 - acc: 0.7510 - val_loss: 0.4927 - val_acc: 0.7756\n",
      "Epoch 228/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5440 - acc: 0.7471 - val_loss: 0.4934 - val_acc: 0.7756\n",
      "Epoch 229/2000\n",
      "514/514 [==============================] - 0s 249us/step - loss: 0.5303 - acc: 0.7549 - val_loss: 0.4970 - val_acc: 0.7677\n",
      "Epoch 230/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.5276 - acc: 0.7510 - val_loss: 0.4961 - val_acc: 0.7795\n",
      "Epoch 231/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5147 - acc: 0.7704 - val_loss: 0.4956 - val_acc: 0.7717\n",
      "Epoch 232/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5597 - acc: 0.7315 - val_loss: 0.4942 - val_acc: 0.7795\n",
      "Epoch 233/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5254 - acc: 0.7354 - val_loss: 0.4955 - val_acc: 0.7874\n",
      "Epoch 234/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5266 - acc: 0.7626 - val_loss: 0.4944 - val_acc: 0.7835\n",
      "Epoch 235/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5346 - acc: 0.7354 - val_loss: 0.4957 - val_acc: 0.7756\n",
      "Epoch 236/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5196 - acc: 0.7821 - val_loss: 0.4960 - val_acc: 0.7717\n",
      "Epoch 237/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5365 - acc: 0.7374 - val_loss: 0.4944 - val_acc: 0.7717\n",
      "Epoch 238/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 190us/step - loss: 0.5164 - acc: 0.7646 - val_loss: 0.4912 - val_acc: 0.7717\n",
      "Epoch 239/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5451 - acc: 0.7198 - val_loss: 0.4923 - val_acc: 0.7717\n",
      "Epoch 240/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5633 - acc: 0.7315 - val_loss: 0.4934 - val_acc: 0.7756\n",
      "Epoch 241/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5163 - acc: 0.7412 - val_loss: 0.4914 - val_acc: 0.7795\n",
      "Epoch 242/2000\n",
      "514/514 [==============================] - 0s 235us/step - loss: 0.5291 - acc: 0.7549 - val_loss: 0.4901 - val_acc: 0.7795\n",
      "Epoch 243/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.5014 - acc: 0.7626 - val_loss: 0.4901 - val_acc: 0.7756\n",
      "Epoch 244/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5127 - acc: 0.7665 - val_loss: 0.4944 - val_acc: 0.7677\n",
      "Epoch 245/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5185 - acc: 0.7529 - val_loss: 0.4951 - val_acc: 0.7677\n",
      "Epoch 246/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5248 - acc: 0.7412 - val_loss: 0.4966 - val_acc: 0.7638\n",
      "Epoch 247/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5307 - acc: 0.7393 - val_loss: 0.5045 - val_acc: 0.7362\n",
      "Epoch 248/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5387 - acc: 0.7296 - val_loss: 0.4929 - val_acc: 0.7874\n",
      "Epoch 249/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5366 - acc: 0.7335 - val_loss: 0.4935 - val_acc: 0.7874\n",
      "Epoch 250/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5414 - acc: 0.7198 - val_loss: 0.4939 - val_acc: 0.7795\n",
      "Epoch 251/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5141 - acc: 0.7529 - val_loss: 0.4925 - val_acc: 0.7756\n",
      "Epoch 252/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5138 - acc: 0.7626 - val_loss: 0.4925 - val_acc: 0.7756\n",
      "Epoch 253/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5210 - acc: 0.7529 - val_loss: 0.4936 - val_acc: 0.7598\n",
      "Epoch 254/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5098 - acc: 0.7549 - val_loss: 0.4975 - val_acc: 0.7441\n",
      "Epoch 255/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5053 - acc: 0.7646 - val_loss: 0.4932 - val_acc: 0.7677\n",
      "Epoch 256/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5295 - acc: 0.7646 - val_loss: 0.4916 - val_acc: 0.7874\n",
      "Epoch 257/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5179 - acc: 0.7588 - val_loss: 0.4904 - val_acc: 0.7795\n",
      "Epoch 258/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5316 - acc: 0.7354 - val_loss: 0.4898 - val_acc: 0.7835\n",
      "Epoch 259/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.5074 - acc: 0.7315 - val_loss: 0.4901 - val_acc: 0.7835\n",
      "Epoch 260/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.5184 - acc: 0.7257 - val_loss: 0.4903 - val_acc: 0.7717\n",
      "Epoch 261/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5171 - acc: 0.7588 - val_loss: 0.4902 - val_acc: 0.7677\n",
      "Epoch 262/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5229 - acc: 0.7704 - val_loss: 0.4901 - val_acc: 0.7835\n",
      "Epoch 263/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5335 - acc: 0.7412 - val_loss: 0.4928 - val_acc: 0.7598\n",
      "Epoch 264/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5099 - acc: 0.7490 - val_loss: 0.4915 - val_acc: 0.7717\n",
      "Epoch 265/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5320 - acc: 0.7374 - val_loss: 0.4893 - val_acc: 0.7795\n",
      "Epoch 266/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5228 - acc: 0.7490 - val_loss: 0.4888 - val_acc: 0.7874\n",
      "Epoch 267/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5258 - acc: 0.7335 - val_loss: 0.4906 - val_acc: 0.7677\n",
      "Epoch 268/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5353 - acc: 0.7354 - val_loss: 0.4905 - val_acc: 0.7835\n",
      "Epoch 269/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5310 - acc: 0.7393 - val_loss: 0.4895 - val_acc: 0.7795\n",
      "Epoch 270/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5166 - acc: 0.7412 - val_loss: 0.4890 - val_acc: 0.7795\n",
      "Epoch 271/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5251 - acc: 0.7257 - val_loss: 0.4882 - val_acc: 0.7717\n",
      "Epoch 272/2000\n",
      "514/514 [==============================] - 0s 233us/step - loss: 0.5295 - acc: 0.7412 - val_loss: 0.4881 - val_acc: 0.7717\n",
      "Epoch 273/2000\n",
      "514/514 [==============================] - 0s 231us/step - loss: 0.5190 - acc: 0.7529 - val_loss: 0.4914 - val_acc: 0.7559\n",
      "Epoch 274/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5211 - acc: 0.7471 - val_loss: 0.4886 - val_acc: 0.7756\n",
      "Epoch 275/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5337 - acc: 0.7510 - val_loss: 0.4893 - val_acc: 0.7874\n",
      "Epoch 276/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5285 - acc: 0.7412 - val_loss: 0.4897 - val_acc: 0.7756\n",
      "Epoch 277/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5164 - acc: 0.7510 - val_loss: 0.4933 - val_acc: 0.7677\n",
      "Epoch 278/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5437 - acc: 0.7354 - val_loss: 0.4927 - val_acc: 0.7913\n",
      "Epoch 279/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.5212 - acc: 0.7490 - val_loss: 0.4924 - val_acc: 0.7874\n",
      "Epoch 280/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5357 - acc: 0.7412 - val_loss: 0.4930 - val_acc: 0.7953\n",
      "Epoch 281/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.5351 - acc: 0.7549 - val_loss: 0.4965 - val_acc: 0.7677\n",
      "Epoch 282/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5330 - acc: 0.7412 - val_loss: 0.4926 - val_acc: 0.7835\n",
      "Epoch 283/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5214 - acc: 0.7179 - val_loss: 0.4905 - val_acc: 0.7795\n",
      "Epoch 284/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5179 - acc: 0.7724 - val_loss: 0.4923 - val_acc: 0.7756\n",
      "Epoch 285/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4917 - acc: 0.7685 - val_loss: 0.4908 - val_acc: 0.7795\n",
      "Epoch 286/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5048 - acc: 0.7626 - val_loss: 0.4899 - val_acc: 0.7795\n",
      "Epoch 287/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5405 - acc: 0.7237 - val_loss: 0.4894 - val_acc: 0.7795\n",
      "Epoch 288/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5195 - acc: 0.7315 - val_loss: 0.4887 - val_acc: 0.7756\n",
      "Epoch 289/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5290 - acc: 0.7237 - val_loss: 0.4885 - val_acc: 0.7795\n",
      "Epoch 290/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.5296 - acc: 0.7335 - val_loss: 0.4880 - val_acc: 0.7677\n",
      "Epoch 291/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5109 - acc: 0.7549 - val_loss: 0.4908 - val_acc: 0.7677\n",
      "Epoch 292/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5352 - acc: 0.7685 - val_loss: 0.4894 - val_acc: 0.7795\n",
      "Epoch 293/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5099 - acc: 0.7607 - val_loss: 0.4908 - val_acc: 0.7874\n",
      "Epoch 294/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5477 - acc: 0.7315 - val_loss: 0.4939 - val_acc: 0.7717\n",
      "Epoch 295/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5224 - acc: 0.7218 - val_loss: 0.4920 - val_acc: 0.7717\n",
      "Epoch 296/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5235 - acc: 0.7335 - val_loss: 0.4908 - val_acc: 0.7953\n",
      "Epoch 297/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 183us/step - loss: 0.5308 - acc: 0.7490 - val_loss: 0.4903 - val_acc: 0.7795\n",
      "Epoch 298/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5213 - acc: 0.7588 - val_loss: 0.4900 - val_acc: 0.7677\n",
      "Epoch 299/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5219 - acc: 0.7335 - val_loss: 0.4881 - val_acc: 0.7717\n",
      "Epoch 300/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5158 - acc: 0.7665 - val_loss: 0.4896 - val_acc: 0.7992\n",
      "Epoch 301/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5227 - acc: 0.7257 - val_loss: 0.4911 - val_acc: 0.7756\n",
      "Epoch 302/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5119 - acc: 0.7510 - val_loss: 0.4895 - val_acc: 0.7677\n",
      "Epoch 303/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5368 - acc: 0.7471 - val_loss: 0.4895 - val_acc: 0.7874\n",
      "Epoch 304/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5172 - acc: 0.7276 - val_loss: 0.4880 - val_acc: 0.7717\n",
      "Epoch 305/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5234 - acc: 0.7432 - val_loss: 0.4877 - val_acc: 0.7717\n",
      "Epoch 306/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5211 - acc: 0.7588 - val_loss: 0.4889 - val_acc: 0.7598\n",
      "Epoch 307/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5052 - acc: 0.7588 - val_loss: 0.4885 - val_acc: 0.7638\n",
      "Epoch 308/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4990 - acc: 0.7510 - val_loss: 0.4857 - val_acc: 0.7717\n",
      "Epoch 309/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.4944 - acc: 0.7704 - val_loss: 0.4870 - val_acc: 0.7677\n",
      "Epoch 310/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5315 - acc: 0.7607 - val_loss: 0.4866 - val_acc: 0.7638\n",
      "Epoch 311/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5342 - acc: 0.7549 - val_loss: 0.4870 - val_acc: 0.7638\n",
      "Epoch 312/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5312 - acc: 0.7315 - val_loss: 0.4871 - val_acc: 0.7953\n",
      "Epoch 313/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5121 - acc: 0.7626 - val_loss: 0.4867 - val_acc: 0.7677\n",
      "Epoch 314/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5253 - acc: 0.7510 - val_loss: 0.4889 - val_acc: 0.7677\n",
      "Epoch 315/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5672 - acc: 0.7393 - val_loss: 0.5319 - val_acc: 0.7323\n",
      "Epoch 316/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5629 - acc: 0.7101 - val_loss: 0.4977 - val_acc: 0.7835\n",
      "Epoch 317/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5293 - acc: 0.7490 - val_loss: 0.4945 - val_acc: 0.7835\n",
      "Epoch 318/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5290 - acc: 0.7588 - val_loss: 0.4931 - val_acc: 0.7795\n",
      "Epoch 319/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5567 - acc: 0.7374 - val_loss: 0.4952 - val_acc: 0.7874\n",
      "Epoch 320/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5577 - acc: 0.7257 - val_loss: 0.4944 - val_acc: 0.7795\n",
      "Epoch 321/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5136 - acc: 0.7490 - val_loss: 0.4914 - val_acc: 0.7677\n",
      "Epoch 322/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5329 - acc: 0.7218 - val_loss: 0.4912 - val_acc: 0.7795\n",
      "Epoch 323/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5177 - acc: 0.7393 - val_loss: 0.4947 - val_acc: 0.7756\n",
      "Epoch 324/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5385 - acc: 0.7276 - val_loss: 0.4964 - val_acc: 0.7677\n",
      "Epoch 325/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5406 - acc: 0.7257 - val_loss: 0.4888 - val_acc: 0.7677\n",
      "Epoch 326/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5484 - acc: 0.7412 - val_loss: 0.4895 - val_acc: 0.7756\n",
      "Epoch 327/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5357 - acc: 0.7198 - val_loss: 0.4909 - val_acc: 0.7677\n",
      "Epoch 328/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5270 - acc: 0.7179 - val_loss: 0.4927 - val_acc: 0.7717\n",
      "Epoch 329/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5231 - acc: 0.7549 - val_loss: 0.4909 - val_acc: 0.7756\n",
      "Epoch 330/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5217 - acc: 0.7529 - val_loss: 0.4899 - val_acc: 0.7756\n",
      "Epoch 331/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5325 - acc: 0.7276 - val_loss: 0.4900 - val_acc: 0.7717\n",
      "Epoch 332/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5053 - acc: 0.7490 - val_loss: 0.4894 - val_acc: 0.7598\n",
      "Epoch 333/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5278 - acc: 0.7568 - val_loss: 0.4880 - val_acc: 0.7717\n",
      "Epoch 334/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.5036 - acc: 0.7568 - val_loss: 0.4875 - val_acc: 0.7717\n",
      "Epoch 335/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5193 - acc: 0.7471 - val_loss: 0.4899 - val_acc: 0.7717\n",
      "Epoch 336/2000\n",
      "514/514 [==============================] - 0s 219us/step - loss: 0.5313 - acc: 0.7393 - val_loss: 0.4900 - val_acc: 0.7717\n",
      "Epoch 337/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5231 - acc: 0.7335 - val_loss: 0.4916 - val_acc: 0.7717\n",
      "Epoch 338/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5035 - acc: 0.7549 - val_loss: 0.4888 - val_acc: 0.7677\n",
      "Epoch 339/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5138 - acc: 0.7646 - val_loss: 0.4875 - val_acc: 0.7717\n",
      "Epoch 340/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4952 - acc: 0.7860 - val_loss: 0.4861 - val_acc: 0.7677\n",
      "Epoch 341/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5369 - acc: 0.7626 - val_loss: 0.4866 - val_acc: 0.7717\n",
      "Epoch 342/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4923 - acc: 0.7782 - val_loss: 0.4855 - val_acc: 0.7677\n",
      "Epoch 343/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5273 - acc: 0.7451 - val_loss: 0.4865 - val_acc: 0.7756\n",
      "Epoch 344/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5104 - acc: 0.7568 - val_loss: 0.4860 - val_acc: 0.7795\n",
      "Epoch 345/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4968 - acc: 0.7471 - val_loss: 0.4856 - val_acc: 0.7756\n",
      "Epoch 346/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5407 - acc: 0.7529 - val_loss: 0.4838 - val_acc: 0.7756\n",
      "Epoch 347/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5334 - acc: 0.7374 - val_loss: 0.4917 - val_acc: 0.7756\n",
      "Epoch 348/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5267 - acc: 0.7471 - val_loss: 0.4908 - val_acc: 0.7795\n",
      "Epoch 349/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5028 - acc: 0.7510 - val_loss: 0.4832 - val_acc: 0.7638\n",
      "Epoch 350/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5194 - acc: 0.7510 - val_loss: 0.4827 - val_acc: 0.7677\n",
      "Epoch 351/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5043 - acc: 0.7588 - val_loss: 0.4828 - val_acc: 0.7638\n",
      "Epoch 352/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5368 - acc: 0.7471 - val_loss: 0.4837 - val_acc: 0.7677\n",
      "Epoch 353/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5210 - acc: 0.7529 - val_loss: 0.4844 - val_acc: 0.7717\n",
      "Epoch 354/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5183 - acc: 0.7296 - val_loss: 0.4889 - val_acc: 0.7795\n",
      "Epoch 355/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5166 - acc: 0.7626 - val_loss: 0.4844 - val_acc: 0.7756\n",
      "Epoch 356/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 177us/step - loss: 0.5287 - acc: 0.7354 - val_loss: 0.4848 - val_acc: 0.7717\n",
      "Epoch 357/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5318 - acc: 0.7490 - val_loss: 0.4850 - val_acc: 0.7677\n",
      "Epoch 358/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5274 - acc: 0.7412 - val_loss: 0.4891 - val_acc: 0.7795\n",
      "Epoch 359/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5105 - acc: 0.7393 - val_loss: 0.4862 - val_acc: 0.7638\n",
      "Epoch 360/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5079 - acc: 0.7451 - val_loss: 0.4867 - val_acc: 0.7677\n",
      "Epoch 361/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4950 - acc: 0.7646 - val_loss: 0.4855 - val_acc: 0.7677\n",
      "Epoch 362/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.4943 - acc: 0.7432 - val_loss: 0.4837 - val_acc: 0.7795\n",
      "Epoch 363/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5267 - acc: 0.7451 - val_loss: 0.4865 - val_acc: 0.7717\n",
      "Epoch 364/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5538 - acc: 0.7315 - val_loss: 0.4825 - val_acc: 0.7598\n",
      "Epoch 365/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5222 - acc: 0.7510 - val_loss: 0.4865 - val_acc: 0.7795\n",
      "Epoch 366/2000\n",
      "514/514 [==============================] - 0s 173us/step - loss: 0.5182 - acc: 0.7276 - val_loss: 0.4866 - val_acc: 0.7638\n",
      "Epoch 367/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5039 - acc: 0.7412 - val_loss: 0.4862 - val_acc: 0.7598\n",
      "Epoch 368/2000\n",
      "514/514 [==============================] - 0s 173us/step - loss: 0.5268 - acc: 0.7626 - val_loss: 0.4859 - val_acc: 0.7638\n",
      "Epoch 369/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5283 - acc: 0.7315 - val_loss: 0.4868 - val_acc: 0.7835\n",
      "Epoch 370/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5210 - acc: 0.7432 - val_loss: 0.4852 - val_acc: 0.7795\n",
      "Epoch 371/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5296 - acc: 0.7315 - val_loss: 0.4860 - val_acc: 0.7717\n",
      "Epoch 372/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5161 - acc: 0.7374 - val_loss: 0.4862 - val_acc: 0.7677\n",
      "Epoch 373/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4986 - acc: 0.7568 - val_loss: 0.4851 - val_acc: 0.7756\n",
      "Epoch 374/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5311 - acc: 0.7296 - val_loss: 0.4874 - val_acc: 0.7677\n",
      "Epoch 375/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5429 - acc: 0.7374 - val_loss: 0.4902 - val_acc: 0.7717\n",
      "Epoch 376/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5132 - acc: 0.7432 - val_loss: 0.4878 - val_acc: 0.7835\n",
      "Epoch 377/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5334 - acc: 0.7451 - val_loss: 0.4876 - val_acc: 0.7874\n",
      "Epoch 378/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5018 - acc: 0.7607 - val_loss: 0.4866 - val_acc: 0.7756\n",
      "Epoch 379/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5057 - acc: 0.7432 - val_loss: 0.4861 - val_acc: 0.7717\n",
      "Epoch 380/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5101 - acc: 0.7529 - val_loss: 0.4888 - val_acc: 0.7677\n",
      "Epoch 381/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5211 - acc: 0.7354 - val_loss: 0.4870 - val_acc: 0.7756\n",
      "Epoch 382/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.4984 - acc: 0.7743 - val_loss: 0.4871 - val_acc: 0.7677\n",
      "Epoch 383/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5287 - acc: 0.7490 - val_loss: 0.4866 - val_acc: 0.7677\n",
      "Epoch 384/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5281 - acc: 0.7374 - val_loss: 0.4859 - val_acc: 0.7756\n",
      "Epoch 385/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5075 - acc: 0.7451 - val_loss: 0.4864 - val_acc: 0.7717\n",
      "Epoch 386/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5153 - acc: 0.7451 - val_loss: 0.4915 - val_acc: 0.7756\n",
      "Epoch 387/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5182 - acc: 0.7510 - val_loss: 0.4877 - val_acc: 0.7677\n",
      "Epoch 388/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5099 - acc: 0.7393 - val_loss: 0.4870 - val_acc: 0.7717\n",
      "Epoch 389/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5260 - acc: 0.7412 - val_loss: 0.4870 - val_acc: 0.7677\n",
      "Epoch 390/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5354 - acc: 0.7335 - val_loss: 0.4873 - val_acc: 0.7677\n",
      "Epoch 391/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.5114 - acc: 0.7471 - val_loss: 0.4864 - val_acc: 0.7717\n",
      "Epoch 392/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5208 - acc: 0.7588 - val_loss: 0.4858 - val_acc: 0.7756\n",
      "Epoch 393/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5296 - acc: 0.7510 - val_loss: 0.4857 - val_acc: 0.7874\n",
      "Epoch 394/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4933 - acc: 0.7724 - val_loss: 0.4844 - val_acc: 0.7598\n",
      "Epoch 395/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5050 - acc: 0.7335 - val_loss: 0.4853 - val_acc: 0.7756\n",
      "Epoch 396/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4969 - acc: 0.7724 - val_loss: 0.4838 - val_acc: 0.7717\n",
      "Epoch 397/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4958 - acc: 0.7821 - val_loss: 0.4823 - val_acc: 0.7717\n",
      "Epoch 398/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5178 - acc: 0.7529 - val_loss: 0.4825 - val_acc: 0.7795\n",
      "Epoch 399/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5076 - acc: 0.7432 - val_loss: 0.4834 - val_acc: 0.7756\n",
      "Epoch 400/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5005 - acc: 0.7646 - val_loss: 0.4806 - val_acc: 0.7677\n",
      "Epoch 401/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5276 - acc: 0.7646 - val_loss: 0.4804 - val_acc: 0.7717\n",
      "Epoch 402/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5020 - acc: 0.7685 - val_loss: 0.4853 - val_acc: 0.7677\n",
      "Epoch 403/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5031 - acc: 0.7529 - val_loss: 0.4831 - val_acc: 0.7717\n",
      "Epoch 404/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5230 - acc: 0.7549 - val_loss: 0.4846 - val_acc: 0.7795\n",
      "Epoch 405/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4974 - acc: 0.7665 - val_loss: 0.4855 - val_acc: 0.7795\n",
      "Epoch 406/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4977 - acc: 0.7510 - val_loss: 0.4851 - val_acc: 0.7677\n",
      "Epoch 407/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5028 - acc: 0.7451 - val_loss: 0.4847 - val_acc: 0.7756\n",
      "Epoch 408/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5249 - acc: 0.7529 - val_loss: 0.4850 - val_acc: 0.7677\n",
      "Epoch 409/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5158 - acc: 0.7568 - val_loss: 0.4839 - val_acc: 0.7677\n",
      "Epoch 410/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5133 - acc: 0.7568 - val_loss: 0.4853 - val_acc: 0.7717\n",
      "Epoch 411/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5285 - acc: 0.7646 - val_loss: 0.4870 - val_acc: 0.7677\n",
      "Epoch 412/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5271 - acc: 0.7393 - val_loss: 0.4835 - val_acc: 0.7795\n",
      "Epoch 413/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5138 - acc: 0.7451 - val_loss: 0.4850 - val_acc: 0.7717\n",
      "Epoch 414/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5043 - acc: 0.7588 - val_loss: 0.4871 - val_acc: 0.7717\n",
      "Epoch 415/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 190us/step - loss: 0.4942 - acc: 0.7626 - val_loss: 0.4879 - val_acc: 0.7874\n",
      "Epoch 416/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5118 - acc: 0.7451 - val_loss: 0.4885 - val_acc: 0.7795\n",
      "Epoch 417/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5319 - acc: 0.7296 - val_loss: 0.4862 - val_acc: 0.7756\n",
      "Epoch 418/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5017 - acc: 0.7646 - val_loss: 0.4889 - val_acc: 0.7717\n",
      "Epoch 419/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5273 - acc: 0.7374 - val_loss: 0.4889 - val_acc: 0.7756\n",
      "Epoch 420/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5187 - acc: 0.7626 - val_loss: 0.4857 - val_acc: 0.7717\n",
      "Epoch 421/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5248 - acc: 0.7412 - val_loss: 0.4851 - val_acc: 0.7756\n",
      "Epoch 422/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5156 - acc: 0.7354 - val_loss: 0.4846 - val_acc: 0.7756\n",
      "Epoch 423/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5138 - acc: 0.7685 - val_loss: 0.4844 - val_acc: 0.7756\n",
      "Epoch 424/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5127 - acc: 0.7626 - val_loss: 0.4831 - val_acc: 0.7795\n",
      "Epoch 425/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5156 - acc: 0.7374 - val_loss: 0.4834 - val_acc: 0.7717\n",
      "Epoch 426/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5107 - acc: 0.7646 - val_loss: 0.4837 - val_acc: 0.7756\n",
      "Epoch 427/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5296 - acc: 0.7315 - val_loss: 0.4850 - val_acc: 0.7795\n",
      "Epoch 428/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5035 - acc: 0.7588 - val_loss: 0.4864 - val_acc: 0.7717\n",
      "Epoch 429/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5046 - acc: 0.7588 - val_loss: 0.4851 - val_acc: 0.7795\n",
      "Epoch 430/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5304 - acc: 0.7529 - val_loss: 0.4839 - val_acc: 0.7677\n",
      "Epoch 431/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5066 - acc: 0.7510 - val_loss: 0.4844 - val_acc: 0.7677\n",
      "Epoch 432/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5115 - acc: 0.7549 - val_loss: 0.4836 - val_acc: 0.7795\n",
      "Epoch 433/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4979 - acc: 0.7354 - val_loss: 0.4830 - val_acc: 0.7756\n",
      "Epoch 434/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5292 - acc: 0.7451 - val_loss: 0.4832 - val_acc: 0.7795\n",
      "Epoch 435/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5082 - acc: 0.7335 - val_loss: 0.4830 - val_acc: 0.7795\n",
      "Epoch 436/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5116 - acc: 0.7471 - val_loss: 0.4833 - val_acc: 0.7717\n",
      "Epoch 437/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4943 - acc: 0.7549 - val_loss: 0.4833 - val_acc: 0.7795\n",
      "Epoch 438/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5044 - acc: 0.7412 - val_loss: 0.4828 - val_acc: 0.7717\n",
      "Epoch 439/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5234 - acc: 0.7412 - val_loss: 0.4814 - val_acc: 0.7717\n",
      "Epoch 440/2000\n",
      "514/514 [==============================] - 0s 242us/step - loss: 0.5046 - acc: 0.7354 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 441/2000\n",
      "514/514 [==============================] - 0s 227us/step - loss: 0.5198 - acc: 0.7665 - val_loss: 0.4801 - val_acc: 0.7795\n",
      "Epoch 442/2000\n",
      "514/514 [==============================] - 0s 233us/step - loss: 0.5078 - acc: 0.7646 - val_loss: 0.4798 - val_acc: 0.7717\n",
      "Epoch 443/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5196 - acc: 0.7315 - val_loss: 0.4809 - val_acc: 0.7717\n",
      "Epoch 444/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5029 - acc: 0.7568 - val_loss: 0.4824 - val_acc: 0.7795\n",
      "Epoch 445/2000\n",
      "514/514 [==============================] - 0s 280us/step - loss: 0.5282 - acc: 0.7529 - val_loss: 0.4893 - val_acc: 0.7638\n",
      "Epoch 446/2000\n",
      "514/514 [==============================] - 0s 249us/step - loss: 0.5280 - acc: 0.7510 - val_loss: 0.4836 - val_acc: 0.7756\n",
      "Epoch 447/2000\n",
      "514/514 [==============================] - 0s 221us/step - loss: 0.5062 - acc: 0.7665 - val_loss: 0.4864 - val_acc: 0.7795\n",
      "Epoch 448/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5040 - acc: 0.7588 - val_loss: 0.4835 - val_acc: 0.7756\n",
      "Epoch 449/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5244 - acc: 0.7374 - val_loss: 0.4847 - val_acc: 0.7717\n",
      "Epoch 450/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5371 - acc: 0.7529 - val_loss: 0.4908 - val_acc: 0.7677\n",
      "Epoch 451/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4993 - acc: 0.7549 - val_loss: 0.4823 - val_acc: 0.7717\n",
      "Epoch 452/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5335 - acc: 0.7490 - val_loss: 0.4852 - val_acc: 0.7795\n",
      "Epoch 453/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5243 - acc: 0.7393 - val_loss: 0.4831 - val_acc: 0.7795\n",
      "Epoch 454/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5073 - acc: 0.7510 - val_loss: 0.4889 - val_acc: 0.7756\n",
      "Epoch 455/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5174 - acc: 0.7568 - val_loss: 0.4838 - val_acc: 0.7677\n",
      "Epoch 456/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5118 - acc: 0.7335 - val_loss: 0.4831 - val_acc: 0.7835\n",
      "Epoch 457/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5059 - acc: 0.7704 - val_loss: 0.4838 - val_acc: 0.7795\n",
      "Epoch 458/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5130 - acc: 0.7510 - val_loss: 0.4932 - val_acc: 0.7795\n",
      "Epoch 459/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5340 - acc: 0.7335 - val_loss: 0.4899 - val_acc: 0.7756\n",
      "Epoch 460/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5190 - acc: 0.7529 - val_loss: 0.4868 - val_acc: 0.7756\n",
      "Epoch 461/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5059 - acc: 0.7393 - val_loss: 0.4850 - val_acc: 0.7795\n",
      "Epoch 462/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4981 - acc: 0.7451 - val_loss: 0.4842 - val_acc: 0.7756\n",
      "Epoch 463/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5344 - acc: 0.7471 - val_loss: 0.4840 - val_acc: 0.7717\n",
      "Epoch 464/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5174 - acc: 0.7490 - val_loss: 0.4837 - val_acc: 0.7756\n",
      "Epoch 465/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5131 - acc: 0.7626 - val_loss: 0.4840 - val_acc: 0.7677\n",
      "Epoch 466/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5173 - acc: 0.7393 - val_loss: 0.4820 - val_acc: 0.7874\n",
      "Epoch 467/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5011 - acc: 0.7626 - val_loss: 0.4802 - val_acc: 0.7756\n",
      "Epoch 468/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5122 - acc: 0.7374 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 469/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5251 - acc: 0.7529 - val_loss: 0.4812 - val_acc: 0.7756\n",
      "Epoch 470/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4911 - acc: 0.7665 - val_loss: 0.4895 - val_acc: 0.7717\n",
      "Epoch 471/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5142 - acc: 0.7335 - val_loss: 0.4823 - val_acc: 0.7677\n",
      "Epoch 472/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5119 - acc: 0.7529 - val_loss: 0.4855 - val_acc: 0.7677\n",
      "Epoch 473/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5271 - acc: 0.7588 - val_loss: 0.4811 - val_acc: 0.7756\n",
      "Epoch 474/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 192us/step - loss: 0.5055 - acc: 0.7549 - val_loss: 0.4792 - val_acc: 0.7717\n",
      "Epoch 475/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5151 - acc: 0.7393 - val_loss: 0.4820 - val_acc: 0.7795\n",
      "Epoch 476/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5222 - acc: 0.7412 - val_loss: 0.4799 - val_acc: 0.7756\n",
      "Epoch 477/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5361 - acc: 0.7218 - val_loss: 0.4849 - val_acc: 0.7717\n",
      "Epoch 478/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5144 - acc: 0.7451 - val_loss: 0.4819 - val_acc: 0.7756\n",
      "Epoch 479/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5260 - acc: 0.7374 - val_loss: 0.4952 - val_acc: 0.7598\n",
      "Epoch 480/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5338 - acc: 0.7393 - val_loss: 0.4815 - val_acc: 0.7795\n",
      "Epoch 481/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5224 - acc: 0.7588 - val_loss: 0.4808 - val_acc: 0.7756\n",
      "Epoch 482/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5164 - acc: 0.7412 - val_loss: 0.4838 - val_acc: 0.7717\n",
      "Epoch 483/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5161 - acc: 0.7665 - val_loss: 0.4830 - val_acc: 0.7677\n",
      "Epoch 484/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.4994 - acc: 0.7471 - val_loss: 0.4789 - val_acc: 0.7677\n",
      "Epoch 485/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4898 - acc: 0.7626 - val_loss: 0.4778 - val_acc: 0.7677\n",
      "Epoch 486/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5060 - acc: 0.7451 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 487/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5116 - acc: 0.7646 - val_loss: 0.4807 - val_acc: 0.7756\n",
      "Epoch 488/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5172 - acc: 0.7588 - val_loss: 0.4875 - val_acc: 0.7677\n",
      "Epoch 489/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5254 - acc: 0.7374 - val_loss: 0.4846 - val_acc: 0.7756\n",
      "Epoch 490/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5024 - acc: 0.7412 - val_loss: 0.4797 - val_acc: 0.7756\n",
      "Epoch 491/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5060 - acc: 0.7626 - val_loss: 0.4818 - val_acc: 0.7677\n",
      "Epoch 492/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5126 - acc: 0.7374 - val_loss: 0.4824 - val_acc: 0.7795\n",
      "Epoch 493/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5202 - acc: 0.7490 - val_loss: 0.4816 - val_acc: 0.7756\n",
      "Epoch 494/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5079 - acc: 0.7412 - val_loss: 0.4816 - val_acc: 0.7795\n",
      "Epoch 495/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.4913 - acc: 0.7510 - val_loss: 0.4795 - val_acc: 0.7756\n",
      "Epoch 496/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5107 - acc: 0.7549 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 497/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5089 - acc: 0.7471 - val_loss: 0.4800 - val_acc: 0.7795\n",
      "Epoch 498/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5070 - acc: 0.7588 - val_loss: 0.4816 - val_acc: 0.7795\n",
      "Epoch 499/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5271 - acc: 0.7549 - val_loss: 0.4797 - val_acc: 0.7717\n",
      "Epoch 500/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4969 - acc: 0.7451 - val_loss: 0.4812 - val_acc: 0.7756\n",
      "Epoch 501/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4976 - acc: 0.7490 - val_loss: 0.4843 - val_acc: 0.7756\n",
      "Epoch 502/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4914 - acc: 0.7626 - val_loss: 0.4821 - val_acc: 0.7756\n",
      "Epoch 503/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5358 - acc: 0.7840 - val_loss: 0.4831 - val_acc: 0.7717\n",
      "Epoch 504/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5180 - acc: 0.7432 - val_loss: 0.4800 - val_acc: 0.7717\n",
      "Epoch 505/2000\n",
      "514/514 [==============================] - 0s 225us/step - loss: 0.5253 - acc: 0.7354 - val_loss: 0.4810 - val_acc: 0.7795\n",
      "Epoch 506/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5145 - acc: 0.7451 - val_loss: 0.4827 - val_acc: 0.7717\n",
      "Epoch 507/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5330 - acc: 0.7374 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 508/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5188 - acc: 0.7218 - val_loss: 0.4779 - val_acc: 0.7913\n",
      "Epoch 509/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5277 - acc: 0.7276 - val_loss: 0.4800 - val_acc: 0.7717\n",
      "Epoch 510/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4980 - acc: 0.7451 - val_loss: 0.4811 - val_acc: 0.7756\n",
      "Epoch 511/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5404 - acc: 0.7296 - val_loss: 0.4784 - val_acc: 0.7717\n",
      "Epoch 512/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5086 - acc: 0.7354 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 513/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5407 - acc: 0.7451 - val_loss: 0.4818 - val_acc: 0.7874\n",
      "Epoch 514/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5277 - acc: 0.7198 - val_loss: 0.4875 - val_acc: 0.7677\n",
      "Epoch 515/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4875 - acc: 0.7490 - val_loss: 0.4832 - val_acc: 0.7795\n",
      "Epoch 516/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5172 - acc: 0.7646 - val_loss: 0.4931 - val_acc: 0.7795\n",
      "Epoch 517/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5281 - acc: 0.7198 - val_loss: 0.4777 - val_acc: 0.7717\n",
      "Epoch 518/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5111 - acc: 0.7471 - val_loss: 0.4794 - val_acc: 0.7677\n",
      "Epoch 519/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5557 - acc: 0.7004 - val_loss: 0.4821 - val_acc: 0.7677\n",
      "Epoch 520/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5070 - acc: 0.7665 - val_loss: 0.4828 - val_acc: 0.7756\n",
      "Epoch 521/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5295 - acc: 0.7393 - val_loss: 0.4782 - val_acc: 0.7795\n",
      "Epoch 522/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5273 - acc: 0.7335 - val_loss: 0.4766 - val_acc: 0.7795\n",
      "Epoch 523/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5064 - acc: 0.7607 - val_loss: 0.4797 - val_acc: 0.7717\n",
      "Epoch 524/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5253 - acc: 0.7432 - val_loss: 0.4795 - val_acc: 0.7677\n",
      "Epoch 525/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4928 - acc: 0.7588 - val_loss: 0.4797 - val_acc: 0.7677\n",
      "Epoch 526/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5076 - acc: 0.7529 - val_loss: 0.4834 - val_acc: 0.7677\n",
      "Epoch 527/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4992 - acc: 0.7471 - val_loss: 0.4808 - val_acc: 0.7638\n",
      "Epoch 528/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5196 - acc: 0.7490 - val_loss: 0.4792 - val_acc: 0.7638\n",
      "Epoch 529/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5016 - acc: 0.7432 - val_loss: 0.4825 - val_acc: 0.7638\n",
      "Epoch 530/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4997 - acc: 0.7432 - val_loss: 0.4790 - val_acc: 0.7756\n",
      "Epoch 531/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5169 - acc: 0.7412 - val_loss: 0.4820 - val_acc: 0.7756\n",
      "Epoch 532/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5275 - acc: 0.7568 - val_loss: 0.4800 - val_acc: 0.7717\n",
      "Epoch 533/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 182us/step - loss: 0.5172 - acc: 0.7451 - val_loss: 0.4769 - val_acc: 0.7677\n",
      "Epoch 534/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5072 - acc: 0.7374 - val_loss: 0.4801 - val_acc: 0.7677\n",
      "Epoch 535/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4830 - acc: 0.7704 - val_loss: 0.4762 - val_acc: 0.7717\n",
      "Epoch 536/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5152 - acc: 0.7529 - val_loss: 0.4784 - val_acc: 0.7677\n",
      "Epoch 537/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5124 - acc: 0.7685 - val_loss: 0.4777 - val_acc: 0.7717\n",
      "Epoch 538/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5291 - acc: 0.7510 - val_loss: 0.4800 - val_acc: 0.7756\n",
      "Epoch 539/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5138 - acc: 0.7412 - val_loss: 0.4773 - val_acc: 0.7795\n",
      "Epoch 540/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5087 - acc: 0.7451 - val_loss: 0.4781 - val_acc: 0.7717\n",
      "Epoch 541/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5169 - acc: 0.7412 - val_loss: 0.4764 - val_acc: 0.7717\n",
      "Epoch 542/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5116 - acc: 0.7607 - val_loss: 0.4772 - val_acc: 0.7756\n",
      "Epoch 543/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.4960 - acc: 0.7646 - val_loss: 0.4777 - val_acc: 0.7756\n",
      "Epoch 544/2000\n",
      "514/514 [==============================] - 0s 176us/step - loss: 0.5294 - acc: 0.7374 - val_loss: 0.4800 - val_acc: 0.7756\n",
      "Epoch 545/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4978 - acc: 0.7607 - val_loss: 0.4795 - val_acc: 0.7835\n",
      "Epoch 546/2000\n",
      "514/514 [==============================] - 0s 174us/step - loss: 0.5322 - acc: 0.7335 - val_loss: 0.4798 - val_acc: 0.7795\n",
      "Epoch 547/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.4938 - acc: 0.7626 - val_loss: 0.4814 - val_acc: 0.7756\n",
      "Epoch 548/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5245 - acc: 0.7510 - val_loss: 0.4810 - val_acc: 0.7717\n",
      "Epoch 549/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5015 - acc: 0.7626 - val_loss: 0.4792 - val_acc: 0.7795\n",
      "Epoch 550/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5146 - acc: 0.7529 - val_loss: 0.4770 - val_acc: 0.7835\n",
      "Epoch 551/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5144 - acc: 0.7724 - val_loss: 0.4774 - val_acc: 0.7835\n",
      "Epoch 552/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5004 - acc: 0.7607 - val_loss: 0.4769 - val_acc: 0.7835\n",
      "Epoch 553/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4941 - acc: 0.7724 - val_loss: 0.4759 - val_acc: 0.7677\n",
      "Epoch 554/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5082 - acc: 0.7374 - val_loss: 0.4764 - val_acc: 0.7795\n",
      "Epoch 555/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5090 - acc: 0.7549 - val_loss: 0.4879 - val_acc: 0.7756\n",
      "Epoch 556/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5128 - acc: 0.7451 - val_loss: 0.4787 - val_acc: 0.7717\n",
      "Epoch 557/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5235 - acc: 0.7412 - val_loss: 0.4782 - val_acc: 0.7874\n",
      "Epoch 558/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5168 - acc: 0.7646 - val_loss: 0.4773 - val_acc: 0.7795\n",
      "Epoch 559/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5137 - acc: 0.7549 - val_loss: 0.4781 - val_acc: 0.7756\n",
      "Epoch 560/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5094 - acc: 0.7471 - val_loss: 0.4791 - val_acc: 0.7756\n",
      "Epoch 561/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5043 - acc: 0.7704 - val_loss: 0.4791 - val_acc: 0.7913\n",
      "Epoch 562/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5190 - acc: 0.7626 - val_loss: 0.4781 - val_acc: 0.7756\n",
      "Epoch 563/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5072 - acc: 0.7549 - val_loss: 0.4777 - val_acc: 0.7795\n",
      "Epoch 564/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5087 - acc: 0.7393 - val_loss: 0.4773 - val_acc: 0.7795\n",
      "Epoch 565/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5108 - acc: 0.7412 - val_loss: 0.4785 - val_acc: 0.7835\n",
      "Epoch 566/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5079 - acc: 0.7549 - val_loss: 0.4765 - val_acc: 0.7795\n",
      "Epoch 567/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5166 - acc: 0.7646 - val_loss: 0.4779 - val_acc: 0.7874\n",
      "Epoch 568/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5278 - acc: 0.7471 - val_loss: 0.4784 - val_acc: 0.7756\n",
      "Epoch 569/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5109 - acc: 0.7412 - val_loss: 0.4785 - val_acc: 0.7795\n",
      "Epoch 570/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5516 - acc: 0.7471 - val_loss: 0.4792 - val_acc: 0.7717\n",
      "Epoch 571/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5117 - acc: 0.7393 - val_loss: 0.4801 - val_acc: 0.7756\n",
      "Epoch 572/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4988 - acc: 0.7510 - val_loss: 0.4806 - val_acc: 0.7756\n",
      "Epoch 573/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4985 - acc: 0.7568 - val_loss: 0.4809 - val_acc: 0.7756\n",
      "Epoch 574/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5116 - acc: 0.7276 - val_loss: 0.4840 - val_acc: 0.7835\n",
      "Epoch 575/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4993 - acc: 0.7510 - val_loss: 0.4834 - val_acc: 0.7795\n",
      "Epoch 576/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5230 - acc: 0.7763 - val_loss: 0.4824 - val_acc: 0.7795\n",
      "Epoch 577/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5361 - acc: 0.7432 - val_loss: 0.4800 - val_acc: 0.7717\n",
      "Epoch 578/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4907 - acc: 0.7685 - val_loss: 0.4786 - val_acc: 0.7756\n",
      "Epoch 579/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4858 - acc: 0.7529 - val_loss: 0.4811 - val_acc: 0.7756\n",
      "Epoch 580/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5008 - acc: 0.7471 - val_loss: 0.4799 - val_acc: 0.7835\n",
      "Epoch 581/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5279 - acc: 0.7354 - val_loss: 0.4809 - val_acc: 0.7756\n",
      "Epoch 582/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5211 - acc: 0.7471 - val_loss: 0.4968 - val_acc: 0.7480\n",
      "Epoch 583/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5199 - acc: 0.7529 - val_loss: 0.4808 - val_acc: 0.7953\n",
      "Epoch 584/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5138 - acc: 0.7471 - val_loss: 0.4816 - val_acc: 0.7835\n",
      "Epoch 585/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5372 - acc: 0.7432 - val_loss: 0.5013 - val_acc: 0.7835\n",
      "Epoch 586/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5322 - acc: 0.7510 - val_loss: 0.4870 - val_acc: 0.7874\n",
      "Epoch 587/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5397 - acc: 0.7335 - val_loss: 0.4831 - val_acc: 0.7795\n",
      "Epoch 588/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5030 - acc: 0.7646 - val_loss: 0.4850 - val_acc: 0.7835\n",
      "Epoch 589/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5418 - acc: 0.7335 - val_loss: 0.4819 - val_acc: 0.7835\n",
      "Epoch 590/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5289 - acc: 0.7412 - val_loss: 0.4837 - val_acc: 0.7874\n",
      "Epoch 591/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5193 - acc: 0.7510 - val_loss: 0.4825 - val_acc: 0.7795\n",
      "Epoch 592/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 201us/step - loss: 0.5069 - acc: 0.7451 - val_loss: 0.4830 - val_acc: 0.7756\n",
      "Epoch 593/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4941 - acc: 0.7315 - val_loss: 0.4802 - val_acc: 0.7756\n",
      "Epoch 594/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5050 - acc: 0.7626 - val_loss: 0.4800 - val_acc: 0.7717\n",
      "Epoch 595/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5054 - acc: 0.7412 - val_loss: 0.4818 - val_acc: 0.7874\n",
      "Epoch 596/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5006 - acc: 0.7607 - val_loss: 0.4797 - val_acc: 0.7835\n",
      "Epoch 597/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5007 - acc: 0.7626 - val_loss: 0.4800 - val_acc: 0.7677\n",
      "Epoch 598/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5356 - acc: 0.7335 - val_loss: 0.4795 - val_acc: 0.7756\n",
      "Epoch 599/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4885 - acc: 0.7685 - val_loss: 0.4803 - val_acc: 0.7835\n",
      "Epoch 600/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.4959 - acc: 0.7549 - val_loss: 0.4881 - val_acc: 0.7756\n",
      "Epoch 601/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4979 - acc: 0.7315 - val_loss: 0.4801 - val_acc: 0.7795\n",
      "Epoch 602/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5271 - acc: 0.7568 - val_loss: 0.4786 - val_acc: 0.7835\n",
      "Epoch 603/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5093 - acc: 0.7646 - val_loss: 0.4772 - val_acc: 0.7717\n",
      "Epoch 604/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5434 - acc: 0.7101 - val_loss: 0.4848 - val_acc: 0.7717\n",
      "Epoch 605/2000\n",
      "514/514 [==============================] - 0s 174us/step - loss: 0.4998 - acc: 0.7646 - val_loss: 0.4792 - val_acc: 0.7756\n",
      "Epoch 606/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5142 - acc: 0.7588 - val_loss: 0.4788 - val_acc: 0.7756\n",
      "Epoch 607/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5022 - acc: 0.7296 - val_loss: 0.4882 - val_acc: 0.7638\n",
      "Epoch 608/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5039 - acc: 0.7374 - val_loss: 0.4822 - val_acc: 0.7677\n",
      "Epoch 609/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5125 - acc: 0.7296 - val_loss: 0.4797 - val_acc: 0.7756\n",
      "Epoch 610/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.4951 - acc: 0.7432 - val_loss: 0.4778 - val_acc: 0.7835\n",
      "Epoch 611/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5236 - acc: 0.7315 - val_loss: 0.4753 - val_acc: 0.7795\n",
      "Epoch 612/2000\n",
      "514/514 [==============================] - 0s 175us/step - loss: 0.5161 - acc: 0.7646 - val_loss: 0.4772 - val_acc: 0.7717\n",
      "Epoch 613/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5038 - acc: 0.7412 - val_loss: 0.4794 - val_acc: 0.7756\n",
      "Epoch 614/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5363 - acc: 0.7218 - val_loss: 0.4805 - val_acc: 0.7992\n",
      "Epoch 615/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5035 - acc: 0.7451 - val_loss: 0.4787 - val_acc: 0.7756\n",
      "Epoch 616/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4994 - acc: 0.7607 - val_loss: 0.4844 - val_acc: 0.7717\n",
      "Epoch 617/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5099 - acc: 0.7626 - val_loss: 0.4833 - val_acc: 0.7795\n",
      "Epoch 618/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5348 - acc: 0.7335 - val_loss: 0.4831 - val_acc: 0.7756\n",
      "Epoch 619/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.5110 - acc: 0.7665 - val_loss: 0.4855 - val_acc: 0.7717\n",
      "Epoch 620/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.5026 - acc: 0.7451 - val_loss: 0.4836 - val_acc: 0.7717\n",
      "Epoch 621/2000\n",
      "514/514 [==============================] - 0s 174us/step - loss: 0.5117 - acc: 0.7529 - val_loss: 0.4783 - val_acc: 0.7795\n",
      "Epoch 622/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.4954 - acc: 0.7607 - val_loss: 0.4789 - val_acc: 0.7795\n",
      "Epoch 623/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5059 - acc: 0.7432 - val_loss: 0.4845 - val_acc: 0.7717\n",
      "Epoch 624/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5237 - acc: 0.7588 - val_loss: 0.4939 - val_acc: 0.7520\n",
      "Epoch 625/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5054 - acc: 0.7568 - val_loss: 0.4783 - val_acc: 0.7795\n",
      "Epoch 626/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4984 - acc: 0.7724 - val_loss: 0.4769 - val_acc: 0.7835\n",
      "Epoch 627/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5094 - acc: 0.7315 - val_loss: 0.4765 - val_acc: 0.7835\n",
      "Epoch 628/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4813 - acc: 0.7588 - val_loss: 0.4789 - val_acc: 0.7795\n",
      "Epoch 629/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4827 - acc: 0.7724 - val_loss: 0.4790 - val_acc: 0.7677\n",
      "Epoch 630/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4934 - acc: 0.7782 - val_loss: 0.4749 - val_acc: 0.7795\n",
      "Epoch 631/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5073 - acc: 0.7568 - val_loss: 0.4811 - val_acc: 0.7874\n",
      "Epoch 632/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5153 - acc: 0.7626 - val_loss: 0.4778 - val_acc: 0.7835\n",
      "Epoch 633/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4810 - acc: 0.7257 - val_loss: 0.4780 - val_acc: 0.7874\n",
      "Epoch 634/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4971 - acc: 0.7626 - val_loss: 0.4815 - val_acc: 0.7835\n",
      "Epoch 635/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5025 - acc: 0.7685 - val_loss: 0.4809 - val_acc: 0.7835\n",
      "Epoch 636/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4978 - acc: 0.7646 - val_loss: 0.4908 - val_acc: 0.7835\n",
      "Epoch 637/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5369 - acc: 0.7315 - val_loss: 0.4824 - val_acc: 0.7953\n",
      "Epoch 638/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5143 - acc: 0.7510 - val_loss: 0.4782 - val_acc: 0.7913\n",
      "Epoch 639/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5240 - acc: 0.7529 - val_loss: 0.4782 - val_acc: 0.7874\n",
      "Epoch 640/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5161 - acc: 0.7510 - val_loss: 0.4776 - val_acc: 0.7913\n",
      "Epoch 641/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5274 - acc: 0.7237 - val_loss: 0.4769 - val_acc: 0.7874\n",
      "Epoch 642/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5045 - acc: 0.7490 - val_loss: 0.4774 - val_acc: 0.7835\n",
      "Epoch 643/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.4933 - acc: 0.7724 - val_loss: 0.4761 - val_acc: 0.7913\n",
      "Epoch 644/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5107 - acc: 0.7568 - val_loss: 0.4759 - val_acc: 0.7874\n",
      "Epoch 645/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5029 - acc: 0.7510 - val_loss: 0.4794 - val_acc: 0.7913\n",
      "Epoch 646/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5154 - acc: 0.7646 - val_loss: 0.4800 - val_acc: 0.7835\n",
      "Epoch 647/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4830 - acc: 0.7607 - val_loss: 0.4784 - val_acc: 0.7835\n",
      "Epoch 648/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4928 - acc: 0.7490 - val_loss: 0.4787 - val_acc: 0.7874\n",
      "Epoch 649/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5038 - acc: 0.7393 - val_loss: 0.4815 - val_acc: 0.7795\n",
      "Epoch 650/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5209 - acc: 0.7471 - val_loss: 0.4801 - val_acc: 0.7795\n",
      "Epoch 651/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 189us/step - loss: 0.5170 - acc: 0.7335 - val_loss: 0.4774 - val_acc: 0.7835\n",
      "Epoch 652/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4979 - acc: 0.7471 - val_loss: 0.4764 - val_acc: 0.7874\n",
      "Epoch 653/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5186 - acc: 0.7549 - val_loss: 0.4759 - val_acc: 0.7874\n",
      "Epoch 654/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5106 - acc: 0.7665 - val_loss: 0.4787 - val_acc: 0.7913\n",
      "Epoch 655/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5268 - acc: 0.7471 - val_loss: 0.4915 - val_acc: 0.7717\n",
      "Epoch 656/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5267 - acc: 0.7237 - val_loss: 0.4877 - val_acc: 0.7874\n",
      "Epoch 657/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4967 - acc: 0.7646 - val_loss: 0.4884 - val_acc: 0.7874\n",
      "Epoch 658/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.4945 - acc: 0.7646 - val_loss: 0.4845 - val_acc: 0.7913\n",
      "Epoch 659/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.4929 - acc: 0.7626 - val_loss: 0.4831 - val_acc: 0.7874\n",
      "Epoch 660/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4995 - acc: 0.7432 - val_loss: 0.4828 - val_acc: 0.7913\n",
      "Epoch 661/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5332 - acc: 0.7412 - val_loss: 0.4830 - val_acc: 0.7835\n",
      "Epoch 662/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4974 - acc: 0.7529 - val_loss: 0.4807 - val_acc: 0.7835\n",
      "Epoch 663/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4963 - acc: 0.7704 - val_loss: 0.4788 - val_acc: 0.7835\n",
      "Epoch 664/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.4973 - acc: 0.7529 - val_loss: 0.4810 - val_acc: 0.7874\n",
      "Epoch 665/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5039 - acc: 0.7724 - val_loss: 0.4805 - val_acc: 0.7795\n",
      "Epoch 666/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5241 - acc: 0.7549 - val_loss: 0.4792 - val_acc: 0.7953\n",
      "Epoch 667/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4913 - acc: 0.7412 - val_loss: 0.4774 - val_acc: 0.7795\n",
      "Epoch 668/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4966 - acc: 0.7607 - val_loss: 0.4809 - val_acc: 0.7795\n",
      "Epoch 669/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5063 - acc: 0.7568 - val_loss: 0.4789 - val_acc: 0.7756\n",
      "Epoch 670/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4950 - acc: 0.7607 - val_loss: 0.4783 - val_acc: 0.7756\n",
      "Epoch 671/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5159 - acc: 0.7335 - val_loss: 0.4819 - val_acc: 0.7677\n",
      "Epoch 672/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5178 - acc: 0.7568 - val_loss: 0.4772 - val_acc: 0.7756\n",
      "Epoch 673/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5070 - acc: 0.7568 - val_loss: 0.4764 - val_acc: 0.7874\n",
      "Epoch 674/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4911 - acc: 0.7315 - val_loss: 0.4817 - val_acc: 0.7835\n",
      "Epoch 675/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4848 - acc: 0.7665 - val_loss: 0.4836 - val_acc: 0.7874\n",
      "Epoch 676/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4955 - acc: 0.7490 - val_loss: 0.4790 - val_acc: 0.7874\n",
      "Epoch 677/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4980 - acc: 0.7704 - val_loss: 0.4808 - val_acc: 0.7795\n",
      "Epoch 678/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4892 - acc: 0.7549 - val_loss: 0.4793 - val_acc: 0.7795\n",
      "Epoch 679/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5028 - acc: 0.7607 - val_loss: 0.4792 - val_acc: 0.7835\n",
      "Epoch 680/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5165 - acc: 0.7607 - val_loss: 0.4814 - val_acc: 0.7756\n",
      "Epoch 681/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5040 - acc: 0.7646 - val_loss: 0.4794 - val_acc: 0.7717\n",
      "Epoch 682/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4855 - acc: 0.7782 - val_loss: 0.4792 - val_acc: 0.7717\n",
      "Epoch 683/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4801 - acc: 0.7782 - val_loss: 0.4776 - val_acc: 0.7874\n",
      "Epoch 684/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5087 - acc: 0.7510 - val_loss: 0.4786 - val_acc: 0.7835\n",
      "Epoch 685/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4955 - acc: 0.7743 - val_loss: 0.4774 - val_acc: 0.7835\n",
      "Epoch 686/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5104 - acc: 0.7471 - val_loss: 0.4767 - val_acc: 0.7835\n",
      "Epoch 687/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4948 - acc: 0.7490 - val_loss: 0.4770 - val_acc: 0.7795\n",
      "Epoch 688/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5069 - acc: 0.7802 - val_loss: 0.4777 - val_acc: 0.7795\n",
      "Epoch 689/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5054 - acc: 0.7588 - val_loss: 0.4777 - val_acc: 0.7756\n",
      "Epoch 690/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5346 - acc: 0.7451 - val_loss: 0.4809 - val_acc: 0.7835\n",
      "Epoch 691/2000\n",
      "514/514 [==============================] - 0s 179us/step - loss: 0.4979 - acc: 0.7412 - val_loss: 0.4806 - val_acc: 0.7874\n",
      "Epoch 692/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4995 - acc: 0.7568 - val_loss: 0.4778 - val_acc: 0.7835\n",
      "Epoch 693/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.4921 - acc: 0.7607 - val_loss: 0.4777 - val_acc: 0.7953\n",
      "Epoch 694/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4893 - acc: 0.7704 - val_loss: 0.4778 - val_acc: 0.7835\n",
      "Epoch 695/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5107 - acc: 0.7315 - val_loss: 0.4781 - val_acc: 0.7835\n",
      "Epoch 696/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4804 - acc: 0.7743 - val_loss: 0.4817 - val_acc: 0.7717\n",
      "Epoch 697/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4978 - acc: 0.7607 - val_loss: 0.4787 - val_acc: 0.7756\n",
      "Epoch 698/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5134 - acc: 0.7568 - val_loss: 0.4797 - val_acc: 0.7756\n",
      "Epoch 699/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5076 - acc: 0.7665 - val_loss: 0.4792 - val_acc: 0.7795\n",
      "Epoch 700/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5065 - acc: 0.7412 - val_loss: 0.4833 - val_acc: 0.7795\n",
      "Epoch 701/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5322 - acc: 0.7471 - val_loss: 0.4848 - val_acc: 0.7795\n",
      "Epoch 702/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5028 - acc: 0.7588 - val_loss: 0.4797 - val_acc: 0.7756\n",
      "Epoch 703/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5058 - acc: 0.7471 - val_loss: 0.4808 - val_acc: 0.7795\n",
      "Epoch 704/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5084 - acc: 0.7471 - val_loss: 0.4812 - val_acc: 0.7874\n",
      "Epoch 705/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4916 - acc: 0.7549 - val_loss: 0.4797 - val_acc: 0.7835\n",
      "Epoch 706/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4914 - acc: 0.7490 - val_loss: 0.4803 - val_acc: 0.7913\n",
      "Epoch 707/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4962 - acc: 0.7568 - val_loss: 0.4816 - val_acc: 0.7913\n",
      "Epoch 708/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5012 - acc: 0.7529 - val_loss: 0.4830 - val_acc: 0.7677\n",
      "Epoch 709/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.5157 - acc: 0.7568 - val_loss: 0.4826 - val_acc: 0.7835\n",
      "Epoch 710/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 189us/step - loss: 0.5101 - acc: 0.7432 - val_loss: 0.4850 - val_acc: 0.7795\n",
      "Epoch 711/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5133 - acc: 0.7490 - val_loss: 0.4841 - val_acc: 0.7874\n",
      "Epoch 712/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5069 - acc: 0.7607 - val_loss: 0.4833 - val_acc: 0.7953\n",
      "Epoch 713/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5066 - acc: 0.7704 - val_loss: 0.4827 - val_acc: 0.7874\n",
      "Epoch 714/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5068 - acc: 0.7626 - val_loss: 0.4851 - val_acc: 0.7717\n",
      "Epoch 715/2000\n",
      "514/514 [==============================] - 0s 180us/step - loss: 0.5192 - acc: 0.7724 - val_loss: 0.4818 - val_acc: 0.7835\n",
      "Epoch 716/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5115 - acc: 0.7529 - val_loss: 0.4834 - val_acc: 0.7874\n",
      "Epoch 717/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5100 - acc: 0.7549 - val_loss: 0.4945 - val_acc: 0.7756\n",
      "Epoch 718/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5225 - acc: 0.7374 - val_loss: 0.4838 - val_acc: 0.7953\n",
      "Epoch 719/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5155 - acc: 0.7412 - val_loss: 0.4820 - val_acc: 0.7874\n",
      "Epoch 720/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4926 - acc: 0.7704 - val_loss: 0.4813 - val_acc: 0.7913\n",
      "Epoch 721/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5046 - acc: 0.7451 - val_loss: 0.4797 - val_acc: 0.7874\n",
      "Epoch 722/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4816 - acc: 0.7918 - val_loss: 0.4800 - val_acc: 0.7913\n",
      "Epoch 723/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5008 - acc: 0.7490 - val_loss: 0.4782 - val_acc: 0.7913\n",
      "Epoch 724/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5211 - acc: 0.7432 - val_loss: 0.4779 - val_acc: 0.7717\n",
      "Epoch 725/2000\n",
      "514/514 [==============================] - 0s 178us/step - loss: 0.5045 - acc: 0.7588 - val_loss: 0.4784 - val_acc: 0.7835\n",
      "Epoch 726/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5087 - acc: 0.7607 - val_loss: 0.4818 - val_acc: 0.7795\n",
      "Epoch 727/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4983 - acc: 0.7782 - val_loss: 0.4804 - val_acc: 0.7874\n",
      "Epoch 728/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4786 - acc: 0.7743 - val_loss: 0.4813 - val_acc: 0.7874\n",
      "Epoch 729/2000\n",
      "514/514 [==============================] - 0s 177us/step - loss: 0.5094 - acc: 0.7704 - val_loss: 0.4801 - val_acc: 0.7835\n",
      "Epoch 730/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4919 - acc: 0.7510 - val_loss: 0.4805 - val_acc: 0.7795\n",
      "Epoch 731/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4919 - acc: 0.7510 - val_loss: 0.4779 - val_acc: 0.7756\n",
      "Epoch 732/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5213 - acc: 0.7412 - val_loss: 0.4778 - val_acc: 0.7874\n",
      "Epoch 733/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5160 - acc: 0.7451 - val_loss: 0.4791 - val_acc: 0.7795\n",
      "Epoch 734/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5129 - acc: 0.7451 - val_loss: 0.4804 - val_acc: 0.7953\n",
      "Epoch 735/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5059 - acc: 0.7685 - val_loss: 0.4793 - val_acc: 0.7835\n",
      "Epoch 736/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5113 - acc: 0.7393 - val_loss: 0.4794 - val_acc: 0.7835\n",
      "Epoch 737/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5043 - acc: 0.7626 - val_loss: 0.4797 - val_acc: 0.7835\n",
      "Epoch 738/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4940 - acc: 0.7276 - val_loss: 0.4794 - val_acc: 0.7795\n",
      "Epoch 739/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5182 - acc: 0.7393 - val_loss: 0.4806 - val_acc: 0.7835\n",
      "Epoch 740/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4906 - acc: 0.7451 - val_loss: 0.4791 - val_acc: 0.7835\n",
      "Epoch 741/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5081 - acc: 0.7335 - val_loss: 0.4789 - val_acc: 0.7756\n",
      "Epoch 742/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4822 - acc: 0.7685 - val_loss: 0.4792 - val_acc: 0.7677\n",
      "Epoch 743/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4976 - acc: 0.7665 - val_loss: 0.4797 - val_acc: 0.7835\n",
      "Epoch 744/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.4840 - acc: 0.7665 - val_loss: 0.4771 - val_acc: 0.7795\n",
      "Epoch 745/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.5083 - acc: 0.7451 - val_loss: 0.4803 - val_acc: 0.7795\n",
      "Epoch 746/2000\n",
      "514/514 [==============================] - 0s 227us/step - loss: 0.5049 - acc: 0.7763 - val_loss: 0.4810 - val_acc: 0.7717\n",
      "Epoch 747/2000\n",
      "514/514 [==============================] - 0s 242us/step - loss: 0.5031 - acc: 0.7490 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 748/2000\n",
      "514/514 [==============================] - 0s 229us/step - loss: 0.4781 - acc: 0.7685 - val_loss: 0.4784 - val_acc: 0.7835\n",
      "Epoch 749/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5154 - acc: 0.7568 - val_loss: 0.4778 - val_acc: 0.7874\n",
      "Epoch 750/2000\n",
      "514/514 [==============================] - 0s 241us/step - loss: 0.5193 - acc: 0.7276 - val_loss: 0.4776 - val_acc: 0.7756\n",
      "Epoch 751/2000\n",
      "514/514 [==============================] - 0s 244us/step - loss: 0.5159 - acc: 0.7412 - val_loss: 0.4784 - val_acc: 0.7795\n",
      "Epoch 752/2000\n",
      "514/514 [==============================] - 0s 218us/step - loss: 0.5030 - acc: 0.7685 - val_loss: 0.4996 - val_acc: 0.7795\n",
      "Epoch 753/2000\n",
      "514/514 [==============================] - 0s 229us/step - loss: 0.4963 - acc: 0.7607 - val_loss: 0.4839 - val_acc: 0.7795\n",
      "Epoch 754/2000\n",
      "514/514 [==============================] - 0s 275us/step - loss: 0.5138 - acc: 0.7588 - val_loss: 0.4789 - val_acc: 0.7835\n",
      "Epoch 755/2000\n",
      "514/514 [==============================] - 0s 224us/step - loss: 0.5085 - acc: 0.7374 - val_loss: 0.4794 - val_acc: 0.7874\n",
      "Epoch 756/2000\n",
      "514/514 [==============================] - 0s 244us/step - loss: 0.4897 - acc: 0.7802 - val_loss: 0.4790 - val_acc: 0.7835\n",
      "Epoch 757/2000\n",
      "514/514 [==============================] - 0s 435us/step - loss: 0.5288 - acc: 0.7451 - val_loss: 0.4846 - val_acc: 0.7795\n",
      "Epoch 758/2000\n",
      "514/514 [==============================] - 0s 292us/step - loss: 0.5054 - acc: 0.7840 - val_loss: 0.4855 - val_acc: 0.7717\n",
      "Epoch 759/2000\n",
      "514/514 [==============================] - 0s 436us/step - loss: 0.5310 - acc: 0.7588 - val_loss: 0.4962 - val_acc: 0.7756\n",
      "Epoch 760/2000\n",
      "514/514 [==============================] - 0s 368us/step - loss: 0.5379 - acc: 0.7471 - val_loss: 0.4863 - val_acc: 0.7953\n",
      "Epoch 761/2000\n",
      "514/514 [==============================] - 0s 371us/step - loss: 0.5221 - acc: 0.7510 - val_loss: 0.4806 - val_acc: 0.7756\n",
      "Epoch 762/2000\n",
      "514/514 [==============================] - 0s 372us/step - loss: 0.5040 - acc: 0.7451 - val_loss: 0.4775 - val_acc: 0.7795\n",
      "Epoch 763/2000\n",
      "514/514 [==============================] - 0s 367us/step - loss: 0.5075 - acc: 0.7451 - val_loss: 0.4774 - val_acc: 0.7835\n",
      "Epoch 764/2000\n",
      "514/514 [==============================] - 0s 331us/step - loss: 0.5035 - acc: 0.7510 - val_loss: 0.4769 - val_acc: 0.7795\n",
      "Epoch 765/2000\n",
      "514/514 [==============================] - 0s 287us/step - loss: 0.5054 - acc: 0.7607 - val_loss: 0.4761 - val_acc: 0.7795\n",
      "Epoch 766/2000\n",
      "514/514 [==============================] - 0s 287us/step - loss: 0.5032 - acc: 0.7510 - val_loss: 0.4754 - val_acc: 0.7835\n",
      "Epoch 767/2000\n",
      "514/514 [==============================] - 0s 246us/step - loss: 0.4995 - acc: 0.7685 - val_loss: 0.4778 - val_acc: 0.7795\n",
      "Epoch 768/2000\n",
      "514/514 [==============================] - 0s 293us/step - loss: 0.5183 - acc: 0.7568 - val_loss: 0.4766 - val_acc: 0.7874\n",
      "Epoch 769/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 247us/step - loss: 0.4910 - acc: 0.7685 - val_loss: 0.4784 - val_acc: 0.7795\n",
      "Epoch 770/2000\n",
      "514/514 [==============================] - 0s 289us/step - loss: 0.4901 - acc: 0.7412 - val_loss: 0.4782 - val_acc: 0.7795\n",
      "Epoch 771/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.5067 - acc: 0.7490 - val_loss: 0.4792 - val_acc: 0.7756\n",
      "Epoch 772/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.5140 - acc: 0.7568 - val_loss: 0.4762 - val_acc: 0.7874\n",
      "Epoch 773/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4985 - acc: 0.7471 - val_loss: 0.4758 - val_acc: 0.7835\n",
      "Epoch 774/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.5194 - acc: 0.7665 - val_loss: 0.4765 - val_acc: 0.7795\n",
      "Epoch 775/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4914 - acc: 0.7607 - val_loss: 0.4794 - val_acc: 0.7756\n",
      "Epoch 776/2000\n",
      "514/514 [==============================] - 0s 260us/step - loss: 0.4985 - acc: 0.7607 - val_loss: 0.4823 - val_acc: 0.7598\n",
      "Epoch 777/2000\n",
      "514/514 [==============================] - 0s 238us/step - loss: 0.5173 - acc: 0.7549 - val_loss: 0.4760 - val_acc: 0.7795\n",
      "Epoch 778/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.4975 - acc: 0.7529 - val_loss: 0.4726 - val_acc: 0.7874\n",
      "Epoch 779/2000\n",
      "514/514 [==============================] - 0s 274us/step - loss: 0.5126 - acc: 0.7529 - val_loss: 0.4763 - val_acc: 0.7835\n",
      "Epoch 780/2000\n",
      "514/514 [==============================] - 0s 329us/step - loss: 0.5238 - acc: 0.7549 - val_loss: 0.4796 - val_acc: 0.7874\n",
      "Epoch 781/2000\n",
      "514/514 [==============================] - 0s 340us/step - loss: 0.5011 - acc: 0.7432 - val_loss: 0.4776 - val_acc: 0.7795\n",
      "Epoch 782/2000\n",
      "514/514 [==============================] - 0s 262us/step - loss: 0.4905 - acc: 0.7704 - val_loss: 0.4764 - val_acc: 0.7913\n",
      "Epoch 783/2000\n",
      "514/514 [==============================] - 0s 271us/step - loss: 0.5055 - acc: 0.7490 - val_loss: 0.4781 - val_acc: 0.7874\n",
      "Epoch 784/2000\n",
      "514/514 [==============================] - 0s 301us/step - loss: 0.5161 - acc: 0.7743 - val_loss: 0.4796 - val_acc: 0.7835\n",
      "Epoch 785/2000\n",
      "514/514 [==============================] - 0s 292us/step - loss: 0.5057 - acc: 0.7529 - val_loss: 0.4794 - val_acc: 0.7835\n",
      "Epoch 786/2000\n",
      "514/514 [==============================] - 0s 275us/step - loss: 0.4992 - acc: 0.7510 - val_loss: 0.4772 - val_acc: 0.7953\n",
      "Epoch 787/2000\n",
      "514/514 [==============================] - 0s 375us/step - loss: 0.5130 - acc: 0.7588 - val_loss: 0.4810 - val_acc: 0.7795\n",
      "Epoch 788/2000\n",
      "514/514 [==============================] - 0s 306us/step - loss: 0.4973 - acc: 0.7549 - val_loss: 0.4764 - val_acc: 0.7835\n",
      "Epoch 789/2000\n",
      "514/514 [==============================] - 0s 265us/step - loss: 0.5100 - acc: 0.7393 - val_loss: 0.4796 - val_acc: 0.7835\n",
      "Epoch 790/2000\n",
      "514/514 [==============================] - 0s 307us/step - loss: 0.5239 - acc: 0.7412 - val_loss: 0.4869 - val_acc: 0.7835\n",
      "Epoch 791/2000\n",
      "514/514 [==============================] - 0s 279us/step - loss: 0.5059 - acc: 0.7354 - val_loss: 0.4851 - val_acc: 0.7874\n",
      "Epoch 792/2000\n",
      "514/514 [==============================] - 0s 257us/step - loss: 0.5152 - acc: 0.7432 - val_loss: 0.4828 - val_acc: 0.7874\n",
      "Epoch 793/2000\n",
      "514/514 [==============================] - 0s 255us/step - loss: 0.5016 - acc: 0.7510 - val_loss: 0.4821 - val_acc: 0.7874\n",
      "Epoch 794/2000\n",
      "514/514 [==============================] - 0s 239us/step - loss: 0.4999 - acc: 0.7432 - val_loss: 0.4822 - val_acc: 0.7835\n",
      "Epoch 795/2000\n",
      "514/514 [==============================] - 0s 287us/step - loss: 0.4973 - acc: 0.7529 - val_loss: 0.4785 - val_acc: 0.7913\n",
      "Epoch 796/2000\n",
      "514/514 [==============================] - 0s 263us/step - loss: 0.5157 - acc: 0.7335 - val_loss: 0.4789 - val_acc: 0.7835\n",
      "Epoch 797/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.5100 - acc: 0.7626 - val_loss: 0.4812 - val_acc: 0.7795\n",
      "Epoch 798/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.4868 - acc: 0.7685 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 799/2000\n",
      "514/514 [==============================] - 0s 239us/step - loss: 0.4973 - acc: 0.7607 - val_loss: 0.4779 - val_acc: 0.7795\n",
      "Epoch 800/2000\n",
      "514/514 [==============================] - 0s 227us/step - loss: 0.5225 - acc: 0.7432 - val_loss: 0.4792 - val_acc: 0.7835\n",
      "Epoch 801/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.5061 - acc: 0.7665 - val_loss: 0.4908 - val_acc: 0.7756\n",
      "Epoch 802/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.5175 - acc: 0.7451 - val_loss: 0.4800 - val_acc: 0.7835\n",
      "Epoch 803/2000\n",
      "514/514 [==============================] - 0s 347us/step - loss: 0.5291 - acc: 0.7354 - val_loss: 0.4793 - val_acc: 0.7835\n",
      "Epoch 804/2000\n",
      "514/514 [==============================] - 0s 227us/step - loss: 0.4820 - acc: 0.7704 - val_loss: 0.4753 - val_acc: 0.7874\n",
      "Epoch 805/2000\n",
      "514/514 [==============================] - 0s 227us/step - loss: 0.5018 - acc: 0.7393 - val_loss: 0.4816 - val_acc: 0.7677\n",
      "Epoch 806/2000\n",
      "514/514 [==============================] - 0s 227us/step - loss: 0.5220 - acc: 0.7646 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 807/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.4976 - acc: 0.7724 - val_loss: 0.4765 - val_acc: 0.7756\n",
      "Epoch 808/2000\n",
      "514/514 [==============================] - 0s 230us/step - loss: 0.5146 - acc: 0.7412 - val_loss: 0.4766 - val_acc: 0.7795\n",
      "Epoch 809/2000\n",
      "514/514 [==============================] - 0s 266us/step - loss: 0.5067 - acc: 0.7626 - val_loss: 0.4774 - val_acc: 0.7795\n",
      "Epoch 810/2000\n",
      "514/514 [==============================] - 0s 292us/step - loss: 0.5170 - acc: 0.7607 - val_loss: 0.4768 - val_acc: 0.7835\n",
      "Epoch 811/2000\n",
      "514/514 [==============================] - 0s 282us/step - loss: 0.5076 - acc: 0.7529 - val_loss: 0.4767 - val_acc: 0.7717\n",
      "Epoch 812/2000\n",
      "514/514 [==============================] - 0s 276us/step - loss: 0.5013 - acc: 0.7549 - val_loss: 0.4836 - val_acc: 0.7638\n",
      "Epoch 813/2000\n",
      "514/514 [==============================] - 0s 275us/step - loss: 0.4875 - acc: 0.7646 - val_loss: 0.4760 - val_acc: 0.7717\n",
      "Epoch 814/2000\n",
      "514/514 [==============================] - 0s 234us/step - loss: 0.5038 - acc: 0.7490 - val_loss: 0.4752 - val_acc: 0.7638\n",
      "Epoch 815/2000\n",
      "514/514 [==============================] - 0s 247us/step - loss: 0.4933 - acc: 0.7529 - val_loss: 0.4776 - val_acc: 0.7717\n",
      "Epoch 816/2000\n",
      "514/514 [==============================] - 0s 410us/step - loss: 0.5282 - acc: 0.7432 - val_loss: 0.4788 - val_acc: 0.7717\n",
      "Epoch 817/2000\n",
      "514/514 [==============================] - 0s 254us/step - loss: 0.4968 - acc: 0.7588 - val_loss: 0.4826 - val_acc: 0.7756\n",
      "Epoch 818/2000\n",
      "514/514 [==============================] - 0s 256us/step - loss: 0.4992 - acc: 0.7588 - val_loss: 0.4798 - val_acc: 0.7756\n",
      "Epoch 819/2000\n",
      "514/514 [==============================] - 0s 340us/step - loss: 0.5110 - acc: 0.7335 - val_loss: 0.4790 - val_acc: 0.7677\n",
      "Epoch 820/2000\n",
      "514/514 [==============================] - 0s 278us/step - loss: 0.5178 - acc: 0.7568 - val_loss: 0.4810 - val_acc: 0.7795\n",
      "Epoch 821/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5114 - acc: 0.7179 - val_loss: 0.4801 - val_acc: 0.7835\n",
      "Epoch 822/2000\n",
      "514/514 [==============================] - 0s 236us/step - loss: 0.5186 - acc: 0.7490 - val_loss: 0.4788 - val_acc: 0.7717\n",
      "Epoch 823/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5170 - acc: 0.7490 - val_loss: 0.4799 - val_acc: 0.7913\n",
      "Epoch 824/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4999 - acc: 0.7665 - val_loss: 0.4826 - val_acc: 0.7835\n",
      "Epoch 825/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5136 - acc: 0.7646 - val_loss: 0.4794 - val_acc: 0.7717\n",
      "Epoch 826/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4996 - acc: 0.7704 - val_loss: 0.4785 - val_acc: 0.7835\n",
      "Epoch 827/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4876 - acc: 0.7451 - val_loss: 0.4775 - val_acc: 0.7795\n",
      "Epoch 828/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 214us/step - loss: 0.4750 - acc: 0.7840 - val_loss: 0.4755 - val_acc: 0.7717\n",
      "Epoch 829/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4806 - acc: 0.7763 - val_loss: 0.4770 - val_acc: 0.7795\n",
      "Epoch 830/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5017 - acc: 0.7588 - val_loss: 0.4808 - val_acc: 0.7835\n",
      "Epoch 831/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4785 - acc: 0.7646 - val_loss: 0.4768 - val_acc: 0.7717\n",
      "Epoch 832/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5254 - acc: 0.7296 - val_loss: 0.4777 - val_acc: 0.7756\n",
      "Epoch 833/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.4957 - acc: 0.7451 - val_loss: 0.4828 - val_acc: 0.7756\n",
      "Epoch 834/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4826 - acc: 0.7568 - val_loss: 0.4776 - val_acc: 0.7717\n",
      "Epoch 835/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4872 - acc: 0.7510 - val_loss: 0.4803 - val_acc: 0.7874\n",
      "Epoch 836/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4983 - acc: 0.7685 - val_loss: 0.4777 - val_acc: 0.7717\n",
      "Epoch 837/2000\n",
      "514/514 [==============================] - 0s 217us/step - loss: 0.5093 - acc: 0.7354 - val_loss: 0.4779 - val_acc: 0.7717\n",
      "Epoch 838/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5127 - acc: 0.7529 - val_loss: 0.4797 - val_acc: 0.7835\n",
      "Epoch 839/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4854 - acc: 0.7393 - val_loss: 0.4787 - val_acc: 0.7835\n",
      "Epoch 840/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4910 - acc: 0.7665 - val_loss: 0.4769 - val_acc: 0.7795\n",
      "Epoch 841/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4931 - acc: 0.7588 - val_loss: 0.4768 - val_acc: 0.7756\n",
      "Epoch 842/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4788 - acc: 0.7588 - val_loss: 0.4762 - val_acc: 0.7795\n",
      "Epoch 843/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4862 - acc: 0.7607 - val_loss: 0.4763 - val_acc: 0.7795\n",
      "Epoch 844/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5026 - acc: 0.7743 - val_loss: 0.4792 - val_acc: 0.7677\n",
      "Epoch 845/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4810 - acc: 0.7899 - val_loss: 0.4775 - val_acc: 0.7717\n",
      "Epoch 846/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5134 - acc: 0.7510 - val_loss: 0.4772 - val_acc: 0.7638\n",
      "Epoch 847/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4785 - acc: 0.7588 - val_loss: 0.4788 - val_acc: 0.7913\n",
      "Epoch 848/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4896 - acc: 0.7588 - val_loss: 0.4774 - val_acc: 0.7874\n",
      "Epoch 849/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4758 - acc: 0.7685 - val_loss: 0.4811 - val_acc: 0.7756\n",
      "Epoch 850/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5059 - acc: 0.7451 - val_loss: 0.4831 - val_acc: 0.7598\n",
      "Epoch 851/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4949 - acc: 0.7840 - val_loss: 0.4800 - val_acc: 0.7795\n",
      "Epoch 852/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5020 - acc: 0.7568 - val_loss: 0.4806 - val_acc: 0.7874\n",
      "Epoch 853/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.4927 - acc: 0.7549 - val_loss: 0.4779 - val_acc: 0.7756\n",
      "Epoch 854/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.4944 - acc: 0.7510 - val_loss: 0.4777 - val_acc: 0.7835\n",
      "Epoch 855/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.4891 - acc: 0.7432 - val_loss: 0.4782 - val_acc: 0.7874\n",
      "Epoch 856/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5022 - acc: 0.7568 - val_loss: 0.4792 - val_acc: 0.7795\n",
      "Epoch 857/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4888 - acc: 0.7568 - val_loss: 0.4793 - val_acc: 0.7756\n",
      "Epoch 858/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4960 - acc: 0.7802 - val_loss: 0.4778 - val_acc: 0.7835\n",
      "Epoch 859/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4847 - acc: 0.7588 - val_loss: 0.4783 - val_acc: 0.7835\n",
      "Epoch 860/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5151 - acc: 0.7646 - val_loss: 0.4792 - val_acc: 0.7756\n",
      "Epoch 861/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.4950 - acc: 0.7782 - val_loss: 0.4779 - val_acc: 0.7795\n",
      "Epoch 862/2000\n",
      "514/514 [==============================] - 0s 245us/step - loss: 0.5198 - acc: 0.7393 - val_loss: 0.4760 - val_acc: 0.7795\n",
      "Epoch 863/2000\n",
      "514/514 [==============================] - 0s 243us/step - loss: 0.5118 - acc: 0.7432 - val_loss: 0.4786 - val_acc: 0.7913\n",
      "Epoch 864/2000\n",
      "514/514 [==============================] - 0s 241us/step - loss: 0.4983 - acc: 0.7529 - val_loss: 0.4819 - val_acc: 0.7835\n",
      "Epoch 865/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4860 - acc: 0.7704 - val_loss: 0.4782 - val_acc: 0.7835\n",
      "Epoch 866/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5023 - acc: 0.7607 - val_loss: 0.4751 - val_acc: 0.7717\n",
      "Epoch 867/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5072 - acc: 0.7490 - val_loss: 0.4758 - val_acc: 0.7795\n",
      "Epoch 868/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5015 - acc: 0.7510 - val_loss: 0.4763 - val_acc: 0.7795\n",
      "Epoch 869/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4977 - acc: 0.7529 - val_loss: 0.4749 - val_acc: 0.7913\n",
      "Epoch 870/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5031 - acc: 0.7549 - val_loss: 0.4781 - val_acc: 0.7835\n",
      "Epoch 871/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4823 - acc: 0.7529 - val_loss: 0.4758 - val_acc: 0.7795\n",
      "Epoch 872/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4747 - acc: 0.7626 - val_loss: 0.4760 - val_acc: 0.7874\n",
      "Epoch 873/2000\n",
      "514/514 [==============================] - 0s 307us/step - loss: 0.5016 - acc: 0.7646 - val_loss: 0.4764 - val_acc: 0.7835\n",
      "Epoch 874/2000\n",
      "514/514 [==============================] - 0s 343us/step - loss: 0.5032 - acc: 0.7549 - val_loss: 0.4765 - val_acc: 0.7756\n",
      "Epoch 875/2000\n",
      "514/514 [==============================] - 0s 292us/step - loss: 0.5250 - acc: 0.7549 - val_loss: 0.4763 - val_acc: 0.7638\n",
      "Epoch 876/2000\n",
      "514/514 [==============================] - 0s 226us/step - loss: 0.4901 - acc: 0.7665 - val_loss: 0.4759 - val_acc: 0.7795\n",
      "Epoch 877/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4861 - acc: 0.7646 - val_loss: 0.4766 - val_acc: 0.7717\n",
      "Epoch 878/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.5029 - acc: 0.7568 - val_loss: 0.4782 - val_acc: 0.7835\n",
      "Epoch 879/2000\n",
      "514/514 [==============================] - 0s 217us/step - loss: 0.5020 - acc: 0.7685 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 880/2000\n",
      "514/514 [==============================] - 0s 231us/step - loss: 0.4883 - acc: 0.7549 - val_loss: 0.4782 - val_acc: 0.7874\n",
      "Epoch 881/2000\n",
      "514/514 [==============================] - 0s 321us/step - loss: 0.4978 - acc: 0.7665 - val_loss: 0.4941 - val_acc: 0.7598\n",
      "Epoch 882/2000\n",
      "514/514 [==============================] - 0s 338us/step - loss: 0.5447 - acc: 0.7296 - val_loss: 0.4864 - val_acc: 0.7756\n",
      "Epoch 883/2000\n",
      "514/514 [==============================] - 0s 242us/step - loss: 0.5146 - acc: 0.7568 - val_loss: 0.4799 - val_acc: 0.7874\n",
      "Epoch 884/2000\n",
      "514/514 [==============================] - 0s 224us/step - loss: 0.4941 - acc: 0.7665 - val_loss: 0.4830 - val_acc: 0.7795\n",
      "Epoch 885/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.5202 - acc: 0.7588 - val_loss: 0.4758 - val_acc: 0.7835\n",
      "Epoch 886/2000\n",
      "514/514 [==============================] - 0s 232us/step - loss: 0.5020 - acc: 0.7588 - val_loss: 0.4762 - val_acc: 0.7835\n",
      "Epoch 887/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 208us/step - loss: 0.4872 - acc: 0.7646 - val_loss: 0.4757 - val_acc: 0.7835\n",
      "Epoch 888/2000\n",
      "514/514 [==============================] - 0s 252us/step - loss: 0.5112 - acc: 0.7626 - val_loss: 0.4769 - val_acc: 0.7874\n",
      "Epoch 889/2000\n",
      "514/514 [==============================] - 0s 348us/step - loss: 0.5185 - acc: 0.7549 - val_loss: 0.4761 - val_acc: 0.7913\n",
      "Epoch 890/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.5246 - acc: 0.7432 - val_loss: 0.4828 - val_acc: 0.7835\n",
      "Epoch 891/2000\n",
      "514/514 [==============================] - 0s 240us/step - loss: 0.5003 - acc: 0.7412 - val_loss: 0.4803 - val_acc: 0.7717\n",
      "Epoch 892/2000\n",
      "514/514 [==============================] - 0s 217us/step - loss: 0.5259 - acc: 0.7393 - val_loss: 0.4774 - val_acc: 0.7795\n",
      "Epoch 893/2000\n",
      "514/514 [==============================] - 0s 223us/step - loss: 0.4956 - acc: 0.7490 - val_loss: 0.4757 - val_acc: 0.7835\n",
      "Epoch 894/2000\n",
      "514/514 [==============================] - 0s 249us/step - loss: 0.5076 - acc: 0.7374 - val_loss: 0.4772 - val_acc: 0.7835\n",
      "Epoch 895/2000\n",
      "514/514 [==============================] - 0s 218us/step - loss: 0.5008 - acc: 0.7529 - val_loss: 0.4776 - val_acc: 0.7835\n",
      "Epoch 896/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.5016 - acc: 0.7393 - val_loss: 0.4847 - val_acc: 0.7874\n",
      "Epoch 897/2000\n",
      "514/514 [==============================] - 0s 219us/step - loss: 0.5083 - acc: 0.7471 - val_loss: 0.4787 - val_acc: 0.7835\n",
      "Epoch 898/2000\n",
      "514/514 [==============================] - 0s 265us/step - loss: 0.4948 - acc: 0.7588 - val_loss: 0.4771 - val_acc: 0.7717\n",
      "Epoch 899/2000\n",
      "514/514 [==============================] - 0s 333us/step - loss: 0.5007 - acc: 0.7451 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 900/2000\n",
      "514/514 [==============================] - 0s 241us/step - loss: 0.4953 - acc: 0.7315 - val_loss: 0.4768 - val_acc: 0.7874\n",
      "Epoch 901/2000\n",
      "514/514 [==============================] - 0s 235us/step - loss: 0.5023 - acc: 0.7607 - val_loss: 0.4756 - val_acc: 0.7874\n",
      "Epoch 902/2000\n",
      "514/514 [==============================] - 0s 219us/step - loss: 0.4826 - acc: 0.7763 - val_loss: 0.4783 - val_acc: 0.7717\n",
      "Epoch 903/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.5149 - acc: 0.7315 - val_loss: 0.4750 - val_acc: 0.7756\n",
      "Epoch 904/2000\n",
      "514/514 [==============================] - 0s 253us/step - loss: 0.4870 - acc: 0.7607 - val_loss: 0.4751 - val_acc: 0.7795\n",
      "Epoch 905/2000\n",
      "514/514 [==============================] - 0s 263us/step - loss: 0.5030 - acc: 0.7490 - val_loss: 0.4760 - val_acc: 0.7795\n",
      "Epoch 906/2000\n",
      "514/514 [==============================] - 0s 225us/step - loss: 0.4792 - acc: 0.7802 - val_loss: 0.4790 - val_acc: 0.7795\n",
      "Epoch 907/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4991 - acc: 0.7451 - val_loss: 0.4737 - val_acc: 0.7795\n",
      "Epoch 908/2000\n",
      "514/514 [==============================] - 0s 224us/step - loss: 0.5210 - acc: 0.7568 - val_loss: 0.4748 - val_acc: 0.7756\n",
      "Epoch 909/2000\n",
      "514/514 [==============================] - 0s 221us/step - loss: 0.4804 - acc: 0.7685 - val_loss: 0.4750 - val_acc: 0.7835\n",
      "Epoch 910/2000\n",
      "514/514 [==============================] - 0s 354us/step - loss: 0.5103 - acc: 0.7665 - val_loss: 0.4747 - val_acc: 0.7835\n",
      "Epoch 911/2000\n",
      "514/514 [==============================] - 0s 260us/step - loss: 0.4962 - acc: 0.7568 - val_loss: 0.4750 - val_acc: 0.7835\n",
      "Epoch 912/2000\n",
      "514/514 [==============================] - 0s 296us/step - loss: 0.4914 - acc: 0.7763 - val_loss: 0.4754 - val_acc: 0.7756\n",
      "Epoch 913/2000\n",
      "514/514 [==============================] - 0s 318us/step - loss: 0.5130 - acc: 0.7374 - val_loss: 0.4748 - val_acc: 0.7835\n",
      "Epoch 914/2000\n",
      "514/514 [==============================] - 0s 269us/step - loss: 0.5278 - acc: 0.7393 - val_loss: 0.4757 - val_acc: 0.7835\n",
      "Epoch 915/2000\n",
      "514/514 [==============================] - 0s 240us/step - loss: 0.5059 - acc: 0.7471 - val_loss: 0.4753 - val_acc: 0.7835\n",
      "Epoch 916/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5003 - acc: 0.7588 - val_loss: 0.4797 - val_acc: 0.7835\n",
      "Epoch 917/2000\n",
      "514/514 [==============================] - 0s 232us/step - loss: 0.4915 - acc: 0.7588 - val_loss: 0.4791 - val_acc: 0.7835\n",
      "Epoch 918/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5048 - acc: 0.7529 - val_loss: 0.4767 - val_acc: 0.7913\n",
      "Epoch 919/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.5070 - acc: 0.7335 - val_loss: 0.4776 - val_acc: 0.7795\n",
      "Epoch 920/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5035 - acc: 0.7510 - val_loss: 0.4773 - val_acc: 0.7795\n",
      "Epoch 921/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4944 - acc: 0.7704 - val_loss: 0.4782 - val_acc: 0.7835\n",
      "Epoch 922/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4945 - acc: 0.7471 - val_loss: 0.4791 - val_acc: 0.7835\n",
      "Epoch 923/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5070 - acc: 0.7510 - val_loss: 0.4788 - val_acc: 0.7874\n",
      "Epoch 924/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4803 - acc: 0.7743 - val_loss: 0.4783 - val_acc: 0.7835\n",
      "Epoch 925/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5114 - acc: 0.7529 - val_loss: 0.4740 - val_acc: 0.7835\n",
      "Epoch 926/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4872 - acc: 0.7899 - val_loss: 0.4739 - val_acc: 0.7835\n",
      "Epoch 927/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4764 - acc: 0.7724 - val_loss: 0.4738 - val_acc: 0.7795\n",
      "Epoch 928/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.4838 - acc: 0.7607 - val_loss: 0.4755 - val_acc: 0.7835\n",
      "Epoch 929/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4933 - acc: 0.7529 - val_loss: 0.4759 - val_acc: 0.7756\n",
      "Epoch 930/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4920 - acc: 0.7743 - val_loss: 0.4762 - val_acc: 0.7756\n",
      "Epoch 931/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4913 - acc: 0.7432 - val_loss: 0.4777 - val_acc: 0.7874\n",
      "Epoch 932/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5028 - acc: 0.7568 - val_loss: 0.4767 - val_acc: 0.7835\n",
      "Epoch 933/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4919 - acc: 0.7724 - val_loss: 0.4790 - val_acc: 0.7835\n",
      "Epoch 934/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5030 - acc: 0.7626 - val_loss: 0.4801 - val_acc: 0.7913\n",
      "Epoch 935/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5104 - acc: 0.7510 - val_loss: 0.4886 - val_acc: 0.7835\n",
      "Epoch 936/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4920 - acc: 0.7743 - val_loss: 0.4817 - val_acc: 0.7874\n",
      "Epoch 937/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.5075 - acc: 0.7432 - val_loss: 0.4785 - val_acc: 0.7874\n",
      "Epoch 938/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5116 - acc: 0.7451 - val_loss: 0.4809 - val_acc: 0.7913\n",
      "Epoch 939/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5131 - acc: 0.7626 - val_loss: 0.4795 - val_acc: 0.7913\n",
      "Epoch 940/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5122 - acc: 0.7412 - val_loss: 0.4824 - val_acc: 0.7835\n",
      "Epoch 941/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5139 - acc: 0.7451 - val_loss: 0.4758 - val_acc: 0.7953\n",
      "Epoch 942/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5188 - acc: 0.7121 - val_loss: 0.4762 - val_acc: 0.7913\n",
      "Epoch 943/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5160 - acc: 0.7529 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 944/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4745 - acc: 0.7860 - val_loss: 0.4794 - val_acc: 0.7913\n",
      "Epoch 945/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4997 - acc: 0.7432 - val_loss: 0.4759 - val_acc: 0.7913\n",
      "Epoch 946/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 199us/step - loss: 0.5075 - acc: 0.7412 - val_loss: 0.4769 - val_acc: 0.7835\n",
      "Epoch 947/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4935 - acc: 0.7490 - val_loss: 0.4769 - val_acc: 0.7835\n",
      "Epoch 948/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4920 - acc: 0.7626 - val_loss: 0.4782 - val_acc: 0.7913\n",
      "Epoch 949/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4955 - acc: 0.7743 - val_loss: 0.4762 - val_acc: 0.7913\n",
      "Epoch 950/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4940 - acc: 0.7374 - val_loss: 0.4744 - val_acc: 0.7874\n",
      "Epoch 951/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5082 - acc: 0.7743 - val_loss: 0.4756 - val_acc: 0.7874\n",
      "Epoch 952/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4890 - acc: 0.7432 - val_loss: 0.4754 - val_acc: 0.7756\n",
      "Epoch 953/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4917 - acc: 0.7393 - val_loss: 0.4790 - val_acc: 0.7835\n",
      "Epoch 954/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5101 - acc: 0.7451 - val_loss: 0.4820 - val_acc: 0.7795\n",
      "Epoch 955/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5170 - acc: 0.7432 - val_loss: 0.4837 - val_acc: 0.7835\n",
      "Epoch 956/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5127 - acc: 0.7237 - val_loss: 0.4911 - val_acc: 0.7717\n",
      "Epoch 957/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5058 - acc: 0.7412 - val_loss: 0.4784 - val_acc: 0.7913\n",
      "Epoch 958/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5059 - acc: 0.7821 - val_loss: 0.4783 - val_acc: 0.7874\n",
      "Epoch 959/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5280 - acc: 0.7432 - val_loss: 0.4859 - val_acc: 0.7756\n",
      "Epoch 960/2000\n",
      "514/514 [==============================] - 0s 218us/step - loss: 0.5085 - acc: 0.7549 - val_loss: 0.4766 - val_acc: 0.7874\n",
      "Epoch 961/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4921 - acc: 0.7451 - val_loss: 0.4769 - val_acc: 0.7717\n",
      "Epoch 962/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.5056 - acc: 0.7704 - val_loss: 0.4760 - val_acc: 0.7874\n",
      "Epoch 963/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4894 - acc: 0.7568 - val_loss: 0.4798 - val_acc: 0.7835\n",
      "Epoch 964/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4989 - acc: 0.7607 - val_loss: 0.4778 - val_acc: 0.7756\n",
      "Epoch 965/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4888 - acc: 0.7412 - val_loss: 0.4768 - val_acc: 0.7795\n",
      "Epoch 966/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5099 - acc: 0.7315 - val_loss: 0.4787 - val_acc: 0.7874\n",
      "Epoch 967/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4737 - acc: 0.7646 - val_loss: 0.4743 - val_acc: 0.7835\n",
      "Epoch 968/2000\n",
      "514/514 [==============================] - 0s 269us/step - loss: 0.5131 - acc: 0.7335 - val_loss: 0.4733 - val_acc: 0.7835\n",
      "Epoch 969/2000\n",
      "514/514 [==============================] - 0s 231us/step - loss: 0.5082 - acc: 0.7626 - val_loss: 0.4729 - val_acc: 0.7874\n",
      "Epoch 970/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5055 - acc: 0.7626 - val_loss: 0.4899 - val_acc: 0.7480\n",
      "Epoch 971/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5262 - acc: 0.7490 - val_loss: 0.4804 - val_acc: 0.7874\n",
      "Epoch 972/2000\n",
      "514/514 [==============================] - 0s 226us/step - loss: 0.5036 - acc: 0.7549 - val_loss: 0.4813 - val_acc: 0.7795\n",
      "Epoch 973/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4925 - acc: 0.7549 - val_loss: 0.4767 - val_acc: 0.7835\n",
      "Epoch 974/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5140 - acc: 0.7510 - val_loss: 0.4744 - val_acc: 0.7953\n",
      "Epoch 975/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4956 - acc: 0.7763 - val_loss: 0.4759 - val_acc: 0.7913\n",
      "Epoch 976/2000\n",
      "514/514 [==============================] - 0s 220us/step - loss: 0.5164 - acc: 0.7510 - val_loss: 0.4912 - val_acc: 0.7598\n",
      "Epoch 977/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.5118 - acc: 0.7549 - val_loss: 0.4778 - val_acc: 0.7795\n",
      "Epoch 978/2000\n",
      "514/514 [==============================] - 0s 234us/step - loss: 0.5158 - acc: 0.7665 - val_loss: 0.4767 - val_acc: 0.8031\n",
      "Epoch 979/2000\n",
      "514/514 [==============================] - 0s 238us/step - loss: 0.5311 - acc: 0.7335 - val_loss: 0.4800 - val_acc: 0.7913\n",
      "Epoch 980/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.5162 - acc: 0.7490 - val_loss: 0.4840 - val_acc: 0.7953\n",
      "Epoch 981/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5034 - acc: 0.7510 - val_loss: 0.4809 - val_acc: 0.7874\n",
      "Epoch 982/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4965 - acc: 0.7490 - val_loss: 0.4803 - val_acc: 0.7874\n",
      "Epoch 983/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5297 - acc: 0.7510 - val_loss: 0.4813 - val_acc: 0.7795\n",
      "Epoch 984/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5061 - acc: 0.7510 - val_loss: 0.4774 - val_acc: 0.7874\n",
      "Epoch 985/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5125 - acc: 0.7510 - val_loss: 0.4790 - val_acc: 0.7835\n",
      "Epoch 986/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4975 - acc: 0.7471 - val_loss: 0.4767 - val_acc: 0.7835\n",
      "Epoch 987/2000\n",
      "514/514 [==============================] - 0s 220us/step - loss: 0.5017 - acc: 0.7237 - val_loss: 0.4770 - val_acc: 0.7874\n",
      "Epoch 988/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.4822 - acc: 0.7588 - val_loss: 0.4750 - val_acc: 0.7874\n",
      "Epoch 989/2000\n",
      "514/514 [==============================] - 0s 220us/step - loss: 0.4907 - acc: 0.7626 - val_loss: 0.4815 - val_acc: 0.7874\n",
      "Epoch 990/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.4902 - acc: 0.7626 - val_loss: 0.4766 - val_acc: 0.7835\n",
      "Epoch 991/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.4762 - acc: 0.7568 - val_loss: 0.4762 - val_acc: 0.7795\n",
      "Epoch 992/2000\n",
      "514/514 [==============================] - 0s 220us/step - loss: 0.5053 - acc: 0.7121 - val_loss: 0.4748 - val_acc: 0.7953\n",
      "Epoch 993/2000\n",
      "514/514 [==============================] - 0s 224us/step - loss: 0.5130 - acc: 0.7471 - val_loss: 0.4758 - val_acc: 0.7913\n",
      "Epoch 994/2000\n",
      "514/514 [==============================] - 0s 238us/step - loss: 0.4788 - acc: 0.7996 - val_loss: 0.4746 - val_acc: 0.7874\n",
      "Epoch 995/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.5302 - acc: 0.7451 - val_loss: 0.4743 - val_acc: 0.7913\n",
      "Epoch 996/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4879 - acc: 0.7782 - val_loss: 0.4800 - val_acc: 0.7913\n",
      "Epoch 997/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4799 - acc: 0.7646 - val_loss: 0.4754 - val_acc: 0.7795\n",
      "Epoch 998/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5150 - acc: 0.7451 - val_loss: 0.4728 - val_acc: 0.7992\n",
      "Epoch 999/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5011 - acc: 0.7471 - val_loss: 0.4755 - val_acc: 0.8031\n",
      "Epoch 1000/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4831 - acc: 0.7354 - val_loss: 0.4764 - val_acc: 0.7913\n",
      "Epoch 1001/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4913 - acc: 0.7646 - val_loss: 0.4773 - val_acc: 0.7874\n",
      "Epoch 1002/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4993 - acc: 0.7490 - val_loss: 0.4772 - val_acc: 0.7913\n",
      "Epoch 1003/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5058 - acc: 0.7646 - val_loss: 0.4762 - val_acc: 0.7835\n",
      "Epoch 1004/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4754 - acc: 0.7529 - val_loss: 0.4762 - val_acc: 0.7795\n",
      "Epoch 1005/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 189us/step - loss: 0.4876 - acc: 0.7607 - val_loss: 0.4734 - val_acc: 0.7835\n",
      "Epoch 1006/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5008 - acc: 0.7802 - val_loss: 0.4741 - val_acc: 0.7874\n",
      "Epoch 1007/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5150 - acc: 0.7393 - val_loss: 0.4754 - val_acc: 0.7913\n",
      "Epoch 1008/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4986 - acc: 0.7451 - val_loss: 0.4787 - val_acc: 0.7756\n",
      "Epoch 1009/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4991 - acc: 0.7549 - val_loss: 0.4789 - val_acc: 0.7795\n",
      "Epoch 1010/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4870 - acc: 0.7490 - val_loss: 0.4768 - val_acc: 0.7795\n",
      "Epoch 1011/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4849 - acc: 0.7724 - val_loss: 0.4750 - val_acc: 0.7913\n",
      "Epoch 1012/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4925 - acc: 0.7704 - val_loss: 0.4780 - val_acc: 0.7677\n",
      "Epoch 1013/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.5041 - acc: 0.7510 - val_loss: 0.4956 - val_acc: 0.7559\n",
      "Epoch 1014/2000\n",
      "514/514 [==============================] - 0s 220us/step - loss: 0.5134 - acc: 0.7529 - val_loss: 0.4868 - val_acc: 0.7756\n",
      "Epoch 1015/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.5202 - acc: 0.7568 - val_loss: 0.4768 - val_acc: 0.7913\n",
      "Epoch 1016/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5108 - acc: 0.7432 - val_loss: 0.4774 - val_acc: 0.7953\n",
      "Epoch 1017/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5105 - acc: 0.7549 - val_loss: 0.4789 - val_acc: 0.7874\n",
      "Epoch 1018/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.5073 - acc: 0.7646 - val_loss: 0.4759 - val_acc: 0.7913\n",
      "Epoch 1019/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4763 - acc: 0.7588 - val_loss: 0.4762 - val_acc: 0.7913\n",
      "Epoch 1020/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5230 - acc: 0.7393 - val_loss: 0.4791 - val_acc: 0.7874\n",
      "Epoch 1021/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5196 - acc: 0.7218 - val_loss: 0.4783 - val_acc: 0.7874\n",
      "Epoch 1022/2000\n",
      "514/514 [==============================] - 0s 218us/step - loss: 0.4986 - acc: 0.7374 - val_loss: 0.4790 - val_acc: 0.7835\n",
      "Epoch 1023/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5014 - acc: 0.7607 - val_loss: 0.4795 - val_acc: 0.7835\n",
      "Epoch 1024/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5082 - acc: 0.7471 - val_loss: 0.4802 - val_acc: 0.7874\n",
      "Epoch 1025/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4803 - acc: 0.7568 - val_loss: 0.4785 - val_acc: 0.7874\n",
      "Epoch 1026/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5227 - acc: 0.7665 - val_loss: 0.4870 - val_acc: 0.7756\n",
      "Epoch 1027/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4925 - acc: 0.7451 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 1028/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5087 - acc: 0.7471 - val_loss: 0.4773 - val_acc: 0.7874\n",
      "Epoch 1029/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4887 - acc: 0.7782 - val_loss: 0.4817 - val_acc: 0.7874\n",
      "Epoch 1030/2000\n",
      "514/514 [==============================] - 0s 217us/step - loss: 0.4978 - acc: 0.7665 - val_loss: 0.4776 - val_acc: 0.7835\n",
      "Epoch 1031/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4821 - acc: 0.7763 - val_loss: 0.4792 - val_acc: 0.7835\n",
      "Epoch 1032/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.4754 - acc: 0.7860 - val_loss: 0.4748 - val_acc: 0.7874\n",
      "Epoch 1033/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4910 - acc: 0.7568 - val_loss: 0.4747 - val_acc: 0.7913\n",
      "Epoch 1034/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4977 - acc: 0.7432 - val_loss: 0.4779 - val_acc: 0.7638\n",
      "Epoch 1035/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.5041 - acc: 0.7782 - val_loss: 0.4763 - val_acc: 0.7677\n",
      "Epoch 1036/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4820 - acc: 0.7782 - val_loss: 0.4759 - val_acc: 0.7638\n",
      "Epoch 1037/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.5171 - acc: 0.7607 - val_loss: 0.4732 - val_acc: 0.7795\n",
      "Epoch 1038/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4923 - acc: 0.7685 - val_loss: 0.4719 - val_acc: 0.7874\n",
      "Epoch 1039/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.4924 - acc: 0.7607 - val_loss: 0.4725 - val_acc: 0.7835\n",
      "Epoch 1040/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4943 - acc: 0.7490 - val_loss: 0.4744 - val_acc: 0.7795\n",
      "Epoch 1041/2000\n",
      "514/514 [==============================] - 0s 223us/step - loss: 0.5004 - acc: 0.7568 - val_loss: 0.4743 - val_acc: 0.7874\n",
      "Epoch 1042/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.5008 - acc: 0.7549 - val_loss: 0.4721 - val_acc: 0.7835\n",
      "Epoch 1043/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.4862 - acc: 0.7704 - val_loss: 0.4758 - val_acc: 0.7795\n",
      "Epoch 1044/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4981 - acc: 0.7374 - val_loss: 0.4802 - val_acc: 0.7795\n",
      "Epoch 1045/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4881 - acc: 0.7821 - val_loss: 0.4768 - val_acc: 0.7874\n",
      "Epoch 1046/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5008 - acc: 0.7451 - val_loss: 0.4748 - val_acc: 0.7795\n",
      "Epoch 1047/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5148 - acc: 0.7782 - val_loss: 0.4733 - val_acc: 0.7835\n",
      "Epoch 1048/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5140 - acc: 0.7588 - val_loss: 0.4740 - val_acc: 0.7795\n",
      "Epoch 1049/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4873 - acc: 0.7704 - val_loss: 0.4732 - val_acc: 0.7874\n",
      "Epoch 1050/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5120 - acc: 0.7510 - val_loss: 0.4861 - val_acc: 0.7559\n",
      "Epoch 1051/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4978 - acc: 0.7549 - val_loss: 0.4768 - val_acc: 0.7795\n",
      "Epoch 1052/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.5104 - acc: 0.7626 - val_loss: 0.4746 - val_acc: 0.7874\n",
      "Epoch 1053/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5042 - acc: 0.7782 - val_loss: 0.4736 - val_acc: 0.7913\n",
      "Epoch 1054/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4827 - acc: 0.7626 - val_loss: 0.4750 - val_acc: 0.7913\n",
      "Epoch 1055/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5042 - acc: 0.7568 - val_loss: 0.4760 - val_acc: 0.7835\n",
      "Epoch 1056/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5302 - acc: 0.7451 - val_loss: 0.4751 - val_acc: 0.7913\n",
      "Epoch 1057/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4665 - acc: 0.7685 - val_loss: 0.4768 - val_acc: 0.7835\n",
      "Epoch 1058/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5137 - acc: 0.7529 - val_loss: 0.4769 - val_acc: 0.7717\n",
      "Epoch 1059/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4886 - acc: 0.7665 - val_loss: 0.4750 - val_acc: 0.7913\n",
      "Epoch 1060/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5272 - acc: 0.7374 - val_loss: 0.4762 - val_acc: 0.7835\n",
      "Epoch 1061/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4878 - acc: 0.7763 - val_loss: 0.4742 - val_acc: 0.7756\n",
      "Epoch 1062/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5032 - acc: 0.7549 - val_loss: 0.4745 - val_acc: 0.7795\n",
      "Epoch 1063/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5192 - acc: 0.7412 - val_loss: 0.4755 - val_acc: 0.7795\n",
      "Epoch 1064/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 188us/step - loss: 0.5075 - acc: 0.7510 - val_loss: 0.4742 - val_acc: 0.7717\n",
      "Epoch 1065/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4935 - acc: 0.7529 - val_loss: 0.4752 - val_acc: 0.7913\n",
      "Epoch 1066/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5128 - acc: 0.7490 - val_loss: 0.4771 - val_acc: 0.7913\n",
      "Epoch 1067/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5057 - acc: 0.7568 - val_loss: 0.4765 - val_acc: 0.7795\n",
      "Epoch 1068/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5027 - acc: 0.7549 - val_loss: 0.4772 - val_acc: 0.7717\n",
      "Epoch 1069/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5192 - acc: 0.7588 - val_loss: 0.4800 - val_acc: 0.7717\n",
      "Epoch 1070/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4999 - acc: 0.7704 - val_loss: 0.4800 - val_acc: 0.7874\n",
      "Epoch 1071/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4864 - acc: 0.7510 - val_loss: 0.4773 - val_acc: 0.7835\n",
      "Epoch 1072/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4985 - acc: 0.7626 - val_loss: 0.4777 - val_acc: 0.7874\n",
      "Epoch 1073/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5137 - acc: 0.7607 - val_loss: 0.4818 - val_acc: 0.7835\n",
      "Epoch 1074/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4889 - acc: 0.7743 - val_loss: 0.4760 - val_acc: 0.7795\n",
      "Epoch 1075/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5011 - acc: 0.7471 - val_loss: 0.4756 - val_acc: 0.7913\n",
      "Epoch 1076/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5067 - acc: 0.7665 - val_loss: 0.4752 - val_acc: 0.7835\n",
      "Epoch 1077/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4968 - acc: 0.7588 - val_loss: 0.4770 - val_acc: 0.7756\n",
      "Epoch 1078/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5070 - acc: 0.7646 - val_loss: 0.4754 - val_acc: 0.7835\n",
      "Epoch 1079/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5103 - acc: 0.7549 - val_loss: 0.4751 - val_acc: 0.7835\n",
      "Epoch 1080/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4814 - acc: 0.7626 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 1081/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5177 - acc: 0.7665 - val_loss: 0.4756 - val_acc: 0.7874\n",
      "Epoch 1082/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4966 - acc: 0.7588 - val_loss: 0.4798 - val_acc: 0.7756\n",
      "Epoch 1083/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4997 - acc: 0.7704 - val_loss: 0.4775 - val_acc: 0.7953\n",
      "Epoch 1084/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5018 - acc: 0.7510 - val_loss: 0.4782 - val_acc: 0.7874\n",
      "Epoch 1085/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4819 - acc: 0.7704 - val_loss: 0.4789 - val_acc: 0.7835\n",
      "Epoch 1086/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4909 - acc: 0.7782 - val_loss: 0.4796 - val_acc: 0.7795\n",
      "Epoch 1087/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4987 - acc: 0.7724 - val_loss: 0.4810 - val_acc: 0.7874\n",
      "Epoch 1088/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5181 - acc: 0.7296 - val_loss: 0.4813 - val_acc: 0.7953\n",
      "Epoch 1089/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5058 - acc: 0.7451 - val_loss: 0.4790 - val_acc: 0.7835\n",
      "Epoch 1090/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4817 - acc: 0.7763 - val_loss: 0.4809 - val_acc: 0.7835\n",
      "Epoch 1091/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4865 - acc: 0.7724 - val_loss: 0.4781 - val_acc: 0.7795\n",
      "Epoch 1092/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4971 - acc: 0.7490 - val_loss: 0.4781 - val_acc: 0.7835\n",
      "Epoch 1093/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4755 - acc: 0.7743 - val_loss: 0.4772 - val_acc: 0.7756\n",
      "Epoch 1094/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4994 - acc: 0.7588 - val_loss: 0.4848 - val_acc: 0.7756\n",
      "Epoch 1095/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4894 - acc: 0.7549 - val_loss: 0.4823 - val_acc: 0.7874\n",
      "Epoch 1096/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5173 - acc: 0.7393 - val_loss: 0.4841 - val_acc: 0.7874\n",
      "Epoch 1097/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5040 - acc: 0.7549 - val_loss: 0.4830 - val_acc: 0.7756\n",
      "Epoch 1098/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4902 - acc: 0.7704 - val_loss: 0.4811 - val_acc: 0.7756\n",
      "Epoch 1099/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5095 - acc: 0.7529 - val_loss: 0.4832 - val_acc: 0.7717\n",
      "Epoch 1100/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5084 - acc: 0.7510 - val_loss: 0.4800 - val_acc: 0.7913\n",
      "Epoch 1101/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4933 - acc: 0.7626 - val_loss: 0.4854 - val_acc: 0.7717\n",
      "Epoch 1102/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5014 - acc: 0.7607 - val_loss: 0.4857 - val_acc: 0.7717\n",
      "Epoch 1103/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5241 - acc: 0.7432 - val_loss: 0.4792 - val_acc: 0.7913\n",
      "Epoch 1104/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4924 - acc: 0.7529 - val_loss: 0.4812 - val_acc: 0.7835\n",
      "Epoch 1105/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4875 - acc: 0.7685 - val_loss: 0.4822 - val_acc: 0.7795\n",
      "Epoch 1106/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4844 - acc: 0.7860 - val_loss: 0.4828 - val_acc: 0.7913\n",
      "Epoch 1107/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4849 - acc: 0.7607 - val_loss: 0.4780 - val_acc: 0.7795\n",
      "Epoch 1108/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5276 - acc: 0.7529 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 1109/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4845 - acc: 0.7646 - val_loss: 0.4791 - val_acc: 0.7874\n",
      "Epoch 1110/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4781 - acc: 0.7685 - val_loss: 0.4813 - val_acc: 0.7638\n",
      "Epoch 1111/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4849 - acc: 0.7568 - val_loss: 0.4813 - val_acc: 0.7638\n",
      "Epoch 1112/2000\n",
      "514/514 [==============================] - 0s 182us/step - loss: 0.5074 - acc: 0.7568 - val_loss: 0.4802 - val_acc: 0.7992\n",
      "Epoch 1113/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5097 - acc: 0.7529 - val_loss: 0.4789 - val_acc: 0.7717\n",
      "Epoch 1114/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4721 - acc: 0.7724 - val_loss: 0.4793 - val_acc: 0.7795\n",
      "Epoch 1115/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5052 - acc: 0.7529 - val_loss: 0.4802 - val_acc: 0.7835\n",
      "Epoch 1116/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4881 - acc: 0.7607 - val_loss: 0.4788 - val_acc: 0.7717\n",
      "Epoch 1117/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5038 - acc: 0.7451 - val_loss: 0.4774 - val_acc: 0.7717\n",
      "Epoch 1118/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4830 - acc: 0.7510 - val_loss: 0.4775 - val_acc: 0.7756\n",
      "Epoch 1119/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5054 - acc: 0.7471 - val_loss: 0.4786 - val_acc: 0.7795\n",
      "Epoch 1120/2000\n",
      "514/514 [==============================] - 0s 218us/step - loss: 0.4985 - acc: 0.7354 - val_loss: 0.4782 - val_acc: 0.7717\n",
      "Epoch 1121/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5129 - acc: 0.7257 - val_loss: 0.4824 - val_acc: 0.7835\n",
      "Epoch 1122/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4880 - acc: 0.7510 - val_loss: 0.4832 - val_acc: 0.7795\n",
      "Epoch 1123/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 198us/step - loss: 0.5071 - acc: 0.7529 - val_loss: 0.4907 - val_acc: 0.7835\n",
      "Epoch 1124/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5138 - acc: 0.7393 - val_loss: 0.4847 - val_acc: 0.7795\n",
      "Epoch 1125/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4904 - acc: 0.7529 - val_loss: 0.4861 - val_acc: 0.7717\n",
      "Epoch 1126/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4852 - acc: 0.7588 - val_loss: 0.4828 - val_acc: 0.7874\n",
      "Epoch 1127/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4754 - acc: 0.7724 - val_loss: 0.4839 - val_acc: 0.7756\n",
      "Epoch 1128/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5109 - acc: 0.7568 - val_loss: 0.4810 - val_acc: 0.7835\n",
      "Epoch 1129/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4875 - acc: 0.7451 - val_loss: 0.4810 - val_acc: 0.7874\n",
      "Epoch 1130/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4702 - acc: 0.7490 - val_loss: 0.4805 - val_acc: 0.7756\n",
      "Epoch 1131/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4907 - acc: 0.7296 - val_loss: 0.4788 - val_acc: 0.7874\n",
      "Epoch 1132/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.4775 - acc: 0.7743 - val_loss: 0.4787 - val_acc: 0.7913\n",
      "Epoch 1133/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5250 - acc: 0.7549 - val_loss: 0.4814 - val_acc: 0.7795\n",
      "Epoch 1134/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5004 - acc: 0.7607 - val_loss: 0.4793 - val_acc: 0.7756\n",
      "Epoch 1135/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4920 - acc: 0.7607 - val_loss: 0.4778 - val_acc: 0.7756\n",
      "Epoch 1136/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4929 - acc: 0.7374 - val_loss: 0.4813 - val_acc: 0.7835\n",
      "Epoch 1137/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4923 - acc: 0.7743 - val_loss: 0.4778 - val_acc: 0.7835\n",
      "Epoch 1138/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4992 - acc: 0.7432 - val_loss: 0.4823 - val_acc: 0.7677\n",
      "Epoch 1139/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4930 - acc: 0.7568 - val_loss: 0.4875 - val_acc: 0.7559\n",
      "Epoch 1140/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4971 - acc: 0.7743 - val_loss: 0.4761 - val_acc: 0.7795\n",
      "Epoch 1141/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5140 - acc: 0.7490 - val_loss: 0.4770 - val_acc: 0.7756\n",
      "Epoch 1142/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5110 - acc: 0.7432 - val_loss: 0.4809 - val_acc: 0.7795\n",
      "Epoch 1143/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5023 - acc: 0.7588 - val_loss: 0.4835 - val_acc: 0.7756\n",
      "Epoch 1144/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5052 - acc: 0.7412 - val_loss: 0.4798 - val_acc: 0.7717\n",
      "Epoch 1145/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5171 - acc: 0.7354 - val_loss: 0.4793 - val_acc: 0.7835\n",
      "Epoch 1146/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4930 - acc: 0.7568 - val_loss: 0.4777 - val_acc: 0.7717\n",
      "Epoch 1147/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5093 - acc: 0.7412 - val_loss: 0.4774 - val_acc: 0.7677\n",
      "Epoch 1148/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4742 - acc: 0.7704 - val_loss: 0.4776 - val_acc: 0.7835\n",
      "Epoch 1149/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5163 - acc: 0.7218 - val_loss: 0.4793 - val_acc: 0.7874\n",
      "Epoch 1150/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4890 - acc: 0.7685 - val_loss: 0.4796 - val_acc: 0.7953\n",
      "Epoch 1151/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4678 - acc: 0.7821 - val_loss: 0.4789 - val_acc: 0.7913\n",
      "Epoch 1152/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4914 - acc: 0.7432 - val_loss: 0.4769 - val_acc: 0.7717\n",
      "Epoch 1153/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4788 - acc: 0.7665 - val_loss: 0.4769 - val_acc: 0.7717\n",
      "Epoch 1154/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4858 - acc: 0.7510 - val_loss: 0.4773 - val_acc: 0.7756\n",
      "Epoch 1155/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4748 - acc: 0.7529 - val_loss: 0.4785 - val_acc: 0.7756\n",
      "Epoch 1156/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4983 - acc: 0.7412 - val_loss: 0.4806 - val_acc: 0.7835\n",
      "Epoch 1157/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4887 - acc: 0.7626 - val_loss: 0.4800 - val_acc: 0.7795\n",
      "Epoch 1158/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4755 - acc: 0.7626 - val_loss: 0.4774 - val_acc: 0.7795\n",
      "Epoch 1159/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4751 - acc: 0.7607 - val_loss: 0.4774 - val_acc: 0.7756\n",
      "Epoch 1160/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4762 - acc: 0.7763 - val_loss: 0.4779 - val_acc: 0.7717\n",
      "Epoch 1161/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5139 - acc: 0.7549 - val_loss: 0.4804 - val_acc: 0.7835\n",
      "Epoch 1162/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5059 - acc: 0.7510 - val_loss: 0.4887 - val_acc: 0.7677\n",
      "Epoch 1163/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5301 - acc: 0.7704 - val_loss: 0.4867 - val_acc: 0.7677\n",
      "Epoch 1164/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4865 - acc: 0.7665 - val_loss: 0.4778 - val_acc: 0.7874\n",
      "Epoch 1165/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5005 - acc: 0.7607 - val_loss: 0.4768 - val_acc: 0.7677\n",
      "Epoch 1166/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4968 - acc: 0.7549 - val_loss: 0.4784 - val_acc: 0.7913\n",
      "Epoch 1167/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5216 - acc: 0.7588 - val_loss: 0.4792 - val_acc: 0.7913\n",
      "Epoch 1168/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5067 - acc: 0.7646 - val_loss: 0.4778 - val_acc: 0.7717\n",
      "Epoch 1169/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5110 - acc: 0.7354 - val_loss: 0.4770 - val_acc: 0.7756\n",
      "Epoch 1170/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5109 - acc: 0.7607 - val_loss: 0.4763 - val_acc: 0.7795\n",
      "Epoch 1171/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5150 - acc: 0.7704 - val_loss: 0.4803 - val_acc: 0.7756\n",
      "Epoch 1172/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5124 - acc: 0.7490 - val_loss: 0.4833 - val_acc: 0.7874\n",
      "Epoch 1173/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5034 - acc: 0.7646 - val_loss: 0.4796 - val_acc: 0.7835\n",
      "Epoch 1174/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4997 - acc: 0.7354 - val_loss: 0.4785 - val_acc: 0.7874\n",
      "Epoch 1175/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5016 - acc: 0.7665 - val_loss: 0.4805 - val_acc: 0.7756\n",
      "Epoch 1176/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5014 - acc: 0.7626 - val_loss: 0.4803 - val_acc: 0.7756\n",
      "Epoch 1177/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5065 - acc: 0.7276 - val_loss: 0.4794 - val_acc: 0.7717\n",
      "Epoch 1178/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5126 - acc: 0.7529 - val_loss: 0.4772 - val_acc: 0.7756\n",
      "Epoch 1179/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4950 - acc: 0.7451 - val_loss: 0.4751 - val_acc: 0.7874\n",
      "Epoch 1180/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5200 - acc: 0.7471 - val_loss: 0.4805 - val_acc: 0.7874\n",
      "Epoch 1181/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5185 - acc: 0.7354 - val_loss: 0.4932 - val_acc: 0.7756\n",
      "Epoch 1182/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 187us/step - loss: 0.5293 - acc: 0.7354 - val_loss: 0.4838 - val_acc: 0.7835\n",
      "Epoch 1183/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4902 - acc: 0.7607 - val_loss: 0.4784 - val_acc: 0.7874\n",
      "Epoch 1184/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4967 - acc: 0.7724 - val_loss: 0.4784 - val_acc: 0.7835\n",
      "Epoch 1185/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5075 - acc: 0.7588 - val_loss: 0.4775 - val_acc: 0.7795\n",
      "Epoch 1186/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4943 - acc: 0.7665 - val_loss: 0.4760 - val_acc: 0.7835\n",
      "Epoch 1187/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5214 - acc: 0.7549 - val_loss: 0.4803 - val_acc: 0.7677\n",
      "Epoch 1188/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5020 - acc: 0.7510 - val_loss: 0.4783 - val_acc: 0.7717\n",
      "Epoch 1189/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4977 - acc: 0.7704 - val_loss: 0.4748 - val_acc: 0.7717\n",
      "Epoch 1190/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4917 - acc: 0.7704 - val_loss: 0.4760 - val_acc: 0.7677\n",
      "Epoch 1191/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5031 - acc: 0.7665 - val_loss: 0.4763 - val_acc: 0.7677\n",
      "Epoch 1192/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5005 - acc: 0.7646 - val_loss: 0.4772 - val_acc: 0.7835\n",
      "Epoch 1193/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4672 - acc: 0.7743 - val_loss: 0.4795 - val_acc: 0.7717\n",
      "Epoch 1194/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4861 - acc: 0.7724 - val_loss: 0.4750 - val_acc: 0.7756\n",
      "Epoch 1195/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5077 - acc: 0.7432 - val_loss: 0.4779 - val_acc: 0.7677\n",
      "Epoch 1196/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4855 - acc: 0.7763 - val_loss: 0.4788 - val_acc: 0.7795\n",
      "Epoch 1197/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5158 - acc: 0.7374 - val_loss: 0.4773 - val_acc: 0.7717\n",
      "Epoch 1198/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4894 - acc: 0.7665 - val_loss: 0.4785 - val_acc: 0.7756\n",
      "Epoch 1199/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4816 - acc: 0.7568 - val_loss: 0.4772 - val_acc: 0.7677\n",
      "Epoch 1200/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5134 - acc: 0.7685 - val_loss: 0.4773 - val_acc: 0.7638\n",
      "Epoch 1201/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4930 - acc: 0.7646 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 1202/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4985 - acc: 0.7568 - val_loss: 0.4806 - val_acc: 0.7756\n",
      "Epoch 1203/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5041 - acc: 0.7704 - val_loss: 0.4807 - val_acc: 0.7756\n",
      "Epoch 1204/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5003 - acc: 0.7588 - val_loss: 0.4820 - val_acc: 0.7717\n",
      "Epoch 1205/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4997 - acc: 0.7568 - val_loss: 0.4802 - val_acc: 0.7756\n",
      "Epoch 1206/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5058 - acc: 0.7451 - val_loss: 0.4809 - val_acc: 0.7717\n",
      "Epoch 1207/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4769 - acc: 0.7510 - val_loss: 0.4809 - val_acc: 0.7835\n",
      "Epoch 1208/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4846 - acc: 0.7510 - val_loss: 0.4782 - val_acc: 0.7756\n",
      "Epoch 1209/2000\n",
      "514/514 [==============================] - 0s 229us/step - loss: 0.5226 - acc: 0.7354 - val_loss: 0.4799 - val_acc: 0.7677\n",
      "Epoch 1210/2000\n",
      "514/514 [==============================] - 0s 181us/step - loss: 0.4693 - acc: 0.7860 - val_loss: 0.4797 - val_acc: 0.7756\n",
      "Epoch 1211/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5196 - acc: 0.7588 - val_loss: 0.4969 - val_acc: 0.7677\n",
      "Epoch 1212/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5000 - acc: 0.7685 - val_loss: 0.4811 - val_acc: 0.7756\n",
      "Epoch 1213/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5212 - acc: 0.7685 - val_loss: 0.4775 - val_acc: 0.7795\n",
      "Epoch 1214/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4853 - acc: 0.7646 - val_loss: 0.4789 - val_acc: 0.7756\n",
      "Epoch 1215/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4857 - acc: 0.7763 - val_loss: 0.4760 - val_acc: 0.7835\n",
      "Epoch 1216/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4973 - acc: 0.7588 - val_loss: 0.4759 - val_acc: 0.7756\n",
      "Epoch 1217/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5036 - acc: 0.7665 - val_loss: 0.4771 - val_acc: 0.7795\n",
      "Epoch 1218/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4872 - acc: 0.7529 - val_loss: 0.4783 - val_acc: 0.7756\n",
      "Epoch 1219/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4927 - acc: 0.7724 - val_loss: 0.4755 - val_acc: 0.7795\n",
      "Epoch 1220/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5150 - acc: 0.7646 - val_loss: 0.4762 - val_acc: 0.7835\n",
      "Epoch 1221/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4850 - acc: 0.7471 - val_loss: 0.4781 - val_acc: 0.7677\n",
      "Epoch 1222/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4790 - acc: 0.7802 - val_loss: 0.4752 - val_acc: 0.7795\n",
      "Epoch 1223/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5051 - acc: 0.7510 - val_loss: 0.4824 - val_acc: 0.7638\n",
      "Epoch 1224/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4940 - acc: 0.7568 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 1225/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5260 - acc: 0.7510 - val_loss: 0.4773 - val_acc: 0.7756\n",
      "Epoch 1226/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4854 - acc: 0.7549 - val_loss: 0.4812 - val_acc: 0.7874\n",
      "Epoch 1227/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4880 - acc: 0.7782 - val_loss: 0.4841 - val_acc: 0.7598\n",
      "Epoch 1228/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5189 - acc: 0.7568 - val_loss: 0.4783 - val_acc: 0.7795\n",
      "Epoch 1229/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4776 - acc: 0.7471 - val_loss: 0.4759 - val_acc: 0.7677\n",
      "Epoch 1230/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4987 - acc: 0.7529 - val_loss: 0.4790 - val_acc: 0.7795\n",
      "Epoch 1231/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4867 - acc: 0.7724 - val_loss: 0.4779 - val_acc: 0.7638\n",
      "Epoch 1232/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4853 - acc: 0.7782 - val_loss: 0.4794 - val_acc: 0.7559\n",
      "Epoch 1233/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4839 - acc: 0.7743 - val_loss: 0.4747 - val_acc: 0.7835\n",
      "Epoch 1234/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4836 - acc: 0.7802 - val_loss: 0.4789 - val_acc: 0.7598\n",
      "Epoch 1235/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5039 - acc: 0.7685 - val_loss: 0.4804 - val_acc: 0.7559\n",
      "Epoch 1236/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4763 - acc: 0.7685 - val_loss: 0.4770 - val_acc: 0.7874\n",
      "Epoch 1237/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4802 - acc: 0.7724 - val_loss: 0.4782 - val_acc: 0.7677\n",
      "Epoch 1238/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5157 - acc: 0.7743 - val_loss: 0.4777 - val_acc: 0.7677\n",
      "Epoch 1239/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4963 - acc: 0.7724 - val_loss: 0.4775 - val_acc: 0.7717\n",
      "Epoch 1240/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4668 - acc: 0.7588 - val_loss: 0.4823 - val_acc: 0.7717\n",
      "Epoch 1241/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 200us/step - loss: 0.4890 - acc: 0.7451 - val_loss: 0.4780 - val_acc: 0.7874\n",
      "Epoch 1242/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4998 - acc: 0.7607 - val_loss: 0.4767 - val_acc: 0.7874\n",
      "Epoch 1243/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4982 - acc: 0.7490 - val_loss: 0.4777 - val_acc: 0.7795\n",
      "Epoch 1244/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4752 - acc: 0.7821 - val_loss: 0.4790 - val_acc: 0.7520\n",
      "Epoch 1245/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4997 - acc: 0.7646 - val_loss: 0.4810 - val_acc: 0.7559\n",
      "Epoch 1246/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4953 - acc: 0.7704 - val_loss: 0.4754 - val_acc: 0.7717\n",
      "Epoch 1247/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4955 - acc: 0.7568 - val_loss: 0.4767 - val_acc: 0.7835\n",
      "Epoch 1248/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5040 - acc: 0.7665 - val_loss: 0.4774 - val_acc: 0.7835\n",
      "Epoch 1249/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4786 - acc: 0.7510 - val_loss: 0.4769 - val_acc: 0.7835\n",
      "Epoch 1250/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4846 - acc: 0.7840 - val_loss: 0.4776 - val_acc: 0.7874\n",
      "Epoch 1251/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4853 - acc: 0.7646 - val_loss: 0.4781 - val_acc: 0.7835\n",
      "Epoch 1252/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4959 - acc: 0.7451 - val_loss: 0.4790 - val_acc: 0.7835\n",
      "Epoch 1253/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4891 - acc: 0.7704 - val_loss: 0.4788 - val_acc: 0.7795\n",
      "Epoch 1254/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4920 - acc: 0.7763 - val_loss: 0.4797 - val_acc: 0.7835\n",
      "Epoch 1255/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4926 - acc: 0.7549 - val_loss: 0.4817 - val_acc: 0.7835\n",
      "Epoch 1256/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4908 - acc: 0.7782 - val_loss: 0.4833 - val_acc: 0.7756\n",
      "Epoch 1257/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4905 - acc: 0.7549 - val_loss: 0.4839 - val_acc: 0.7795\n",
      "Epoch 1258/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4877 - acc: 0.7607 - val_loss: 0.4842 - val_acc: 0.7756\n",
      "Epoch 1259/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4936 - acc: 0.7626 - val_loss: 0.4819 - val_acc: 0.7835\n",
      "Epoch 1260/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5057 - acc: 0.7665 - val_loss: 0.4825 - val_acc: 0.7835\n",
      "Epoch 1261/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4923 - acc: 0.7626 - val_loss: 0.4804 - val_acc: 0.7717\n",
      "Epoch 1262/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5339 - acc: 0.7432 - val_loss: 0.4949 - val_acc: 0.7795\n",
      "Epoch 1263/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4872 - acc: 0.7607 - val_loss: 0.4840 - val_acc: 0.7677\n",
      "Epoch 1264/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5067 - acc: 0.7529 - val_loss: 0.4883 - val_acc: 0.7756\n",
      "Epoch 1265/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5283 - acc: 0.7412 - val_loss: 0.4915 - val_acc: 0.7638\n",
      "Epoch 1266/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5086 - acc: 0.7685 - val_loss: 0.4835 - val_acc: 0.7677\n",
      "Epoch 1267/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5088 - acc: 0.7121 - val_loss: 0.4814 - val_acc: 0.7638\n",
      "Epoch 1268/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4830 - acc: 0.7782 - val_loss: 0.4866 - val_acc: 0.7598\n",
      "Epoch 1269/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4800 - acc: 0.7665 - val_loss: 0.4799 - val_acc: 0.7677\n",
      "Epoch 1270/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5065 - acc: 0.7568 - val_loss: 0.4779 - val_acc: 0.7638\n",
      "Epoch 1271/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4889 - acc: 0.7782 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 1272/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5011 - acc: 0.7626 - val_loss: 0.4804 - val_acc: 0.7835\n",
      "Epoch 1273/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5024 - acc: 0.7432 - val_loss: 0.4795 - val_acc: 0.7717\n",
      "Epoch 1274/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4762 - acc: 0.7821 - val_loss: 0.4798 - val_acc: 0.7717\n",
      "Epoch 1275/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4870 - acc: 0.7704 - val_loss: 0.4820 - val_acc: 0.7717\n",
      "Epoch 1276/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5241 - acc: 0.7568 - val_loss: 0.4972 - val_acc: 0.7677\n",
      "Epoch 1277/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5205 - acc: 0.7743 - val_loss: 0.4874 - val_acc: 0.7756\n",
      "Epoch 1278/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4998 - acc: 0.7529 - val_loss: 0.4852 - val_acc: 0.7835\n",
      "Epoch 1279/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5230 - acc: 0.7257 - val_loss: 0.4838 - val_acc: 0.7756\n",
      "Epoch 1280/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5310 - acc: 0.7451 - val_loss: 0.4801 - val_acc: 0.7795\n",
      "Epoch 1281/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4844 - acc: 0.7607 - val_loss: 0.4802 - val_acc: 0.7717\n",
      "Epoch 1282/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4812 - acc: 0.7685 - val_loss: 0.4801 - val_acc: 0.7874\n",
      "Epoch 1283/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5060 - acc: 0.7529 - val_loss: 0.4798 - val_acc: 0.7874\n",
      "Epoch 1284/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4986 - acc: 0.7626 - val_loss: 0.4802 - val_acc: 0.7835\n",
      "Epoch 1285/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5087 - acc: 0.7685 - val_loss: 0.4828 - val_acc: 0.7795\n",
      "Epoch 1286/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4919 - acc: 0.7471 - val_loss: 0.4799 - val_acc: 0.7795\n",
      "Epoch 1287/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4847 - acc: 0.7549 - val_loss: 0.4802 - val_acc: 0.7756\n",
      "Epoch 1288/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4964 - acc: 0.7412 - val_loss: 0.4796 - val_acc: 0.7756\n",
      "Epoch 1289/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4936 - acc: 0.7685 - val_loss: 0.4798 - val_acc: 0.7874\n",
      "Epoch 1290/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4928 - acc: 0.7549 - val_loss: 0.4848 - val_acc: 0.7677\n",
      "Epoch 1291/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4933 - acc: 0.7743 - val_loss: 0.4778 - val_acc: 0.7717\n",
      "Epoch 1292/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4730 - acc: 0.7646 - val_loss: 0.4915 - val_acc: 0.7598\n",
      "Epoch 1293/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5069 - acc: 0.7626 - val_loss: 0.4792 - val_acc: 0.7756\n",
      "Epoch 1294/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5104 - acc: 0.7763 - val_loss: 0.4842 - val_acc: 0.7835\n",
      "Epoch 1295/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4888 - acc: 0.7374 - val_loss: 0.4845 - val_acc: 0.7756\n",
      "Epoch 1296/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4784 - acc: 0.7607 - val_loss: 0.4814 - val_acc: 0.7677\n",
      "Epoch 1297/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4800 - acc: 0.7724 - val_loss: 0.4849 - val_acc: 0.7559\n",
      "Epoch 1298/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4954 - acc: 0.7763 - val_loss: 0.4818 - val_acc: 0.7598\n",
      "Epoch 1299/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4934 - acc: 0.7685 - val_loss: 0.4848 - val_acc: 0.7677\n",
      "Epoch 1300/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 191us/step - loss: 0.4986 - acc: 0.7471 - val_loss: 0.4817 - val_acc: 0.7835\n",
      "Epoch 1301/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4848 - acc: 0.7626 - val_loss: 0.4799 - val_acc: 0.7756\n",
      "Epoch 1302/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4866 - acc: 0.7782 - val_loss: 0.4788 - val_acc: 0.7717\n",
      "Epoch 1303/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5013 - acc: 0.7549 - val_loss: 0.4779 - val_acc: 0.7717\n",
      "Epoch 1304/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4925 - acc: 0.7490 - val_loss: 0.4787 - val_acc: 0.7677\n",
      "Epoch 1305/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5106 - acc: 0.7374 - val_loss: 0.4816 - val_acc: 0.7835\n",
      "Epoch 1306/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4899 - acc: 0.7393 - val_loss: 0.4827 - val_acc: 0.7835\n",
      "Epoch 1307/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4710 - acc: 0.7646 - val_loss: 0.4801 - val_acc: 0.7756\n",
      "Epoch 1308/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4908 - acc: 0.7549 - val_loss: 0.4815 - val_acc: 0.7717\n",
      "Epoch 1309/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4899 - acc: 0.7685 - val_loss: 0.4821 - val_acc: 0.7835\n",
      "Epoch 1310/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5003 - acc: 0.7665 - val_loss: 0.4827 - val_acc: 0.7677\n",
      "Epoch 1311/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4865 - acc: 0.7646 - val_loss: 0.4846 - val_acc: 0.7795\n",
      "Epoch 1312/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4957 - acc: 0.7451 - val_loss: 0.4841 - val_acc: 0.7835\n",
      "Epoch 1313/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5050 - acc: 0.7568 - val_loss: 0.4811 - val_acc: 0.7717\n",
      "Epoch 1314/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4749 - acc: 0.7763 - val_loss: 0.4812 - val_acc: 0.7717\n",
      "Epoch 1315/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4851 - acc: 0.7685 - val_loss: 0.4815 - val_acc: 0.7677\n",
      "Epoch 1316/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.5076 - acc: 0.7743 - val_loss: 0.4807 - val_acc: 0.7717\n",
      "Epoch 1317/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4784 - acc: 0.7607 - val_loss: 0.4806 - val_acc: 0.7717\n",
      "Epoch 1318/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4933 - acc: 0.7451 - val_loss: 0.4834 - val_acc: 0.7874\n",
      "Epoch 1319/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4906 - acc: 0.7840 - val_loss: 0.4825 - val_acc: 0.7913\n",
      "Epoch 1320/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5430 - acc: 0.7510 - val_loss: 0.4900 - val_acc: 0.7717\n",
      "Epoch 1321/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4982 - acc: 0.7665 - val_loss: 0.4824 - val_acc: 0.7795\n",
      "Epoch 1322/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5012 - acc: 0.7782 - val_loss: 0.4803 - val_acc: 0.7756\n",
      "Epoch 1323/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5140 - acc: 0.7451 - val_loss: 0.4829 - val_acc: 0.7795\n",
      "Epoch 1324/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4983 - acc: 0.7510 - val_loss: 0.4806 - val_acc: 0.7795\n",
      "Epoch 1325/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4821 - acc: 0.7510 - val_loss: 0.4841 - val_acc: 0.7795\n",
      "Epoch 1326/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4753 - acc: 0.7588 - val_loss: 0.4808 - val_acc: 0.7835\n",
      "Epoch 1327/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4702 - acc: 0.7704 - val_loss: 0.4818 - val_acc: 0.7835\n",
      "Epoch 1328/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4898 - acc: 0.7763 - val_loss: 0.4808 - val_acc: 0.7835\n",
      "Epoch 1329/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4741 - acc: 0.7665 - val_loss: 0.4802 - val_acc: 0.7795\n",
      "Epoch 1330/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5170 - acc: 0.7588 - val_loss: 0.4799 - val_acc: 0.7677\n",
      "Epoch 1331/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4856 - acc: 0.7568 - val_loss: 0.4819 - val_acc: 0.7835\n",
      "Epoch 1332/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4922 - acc: 0.7724 - val_loss: 0.4825 - val_acc: 0.7756\n",
      "Epoch 1333/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4938 - acc: 0.7549 - val_loss: 0.4814 - val_acc: 0.7795\n",
      "Epoch 1334/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5006 - acc: 0.7763 - val_loss: 0.4829 - val_acc: 0.7756\n",
      "Epoch 1335/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4945 - acc: 0.7549 - val_loss: 0.4833 - val_acc: 0.7795\n",
      "Epoch 1336/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4937 - acc: 0.7763 - val_loss: 0.4843 - val_acc: 0.7717\n",
      "Epoch 1337/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4913 - acc: 0.7704 - val_loss: 0.4850 - val_acc: 0.7835\n",
      "Epoch 1338/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4844 - acc: 0.7665 - val_loss: 0.4854 - val_acc: 0.7795\n",
      "Epoch 1339/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5191 - acc: 0.7626 - val_loss: 0.4848 - val_acc: 0.7756\n",
      "Epoch 1340/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4890 - acc: 0.7626 - val_loss: 0.4836 - val_acc: 0.7717\n",
      "Epoch 1341/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4707 - acc: 0.7763 - val_loss: 0.4802 - val_acc: 0.7795\n",
      "Epoch 1342/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4876 - acc: 0.7665 - val_loss: 0.4799 - val_acc: 0.7717\n",
      "Epoch 1343/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4938 - acc: 0.7646 - val_loss: 0.4787 - val_acc: 0.7795\n",
      "Epoch 1344/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4907 - acc: 0.7763 - val_loss: 0.4797 - val_acc: 0.7717\n",
      "Epoch 1345/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4967 - acc: 0.7588 - val_loss: 0.4834 - val_acc: 0.7756\n",
      "Epoch 1346/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5395 - acc: 0.7393 - val_loss: 0.4923 - val_acc: 0.7795\n",
      "Epoch 1347/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5031 - acc: 0.7490 - val_loss: 0.4860 - val_acc: 0.7795\n",
      "Epoch 1348/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5012 - acc: 0.7374 - val_loss: 0.4881 - val_acc: 0.7874\n",
      "Epoch 1349/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5091 - acc: 0.7568 - val_loss: 0.4872 - val_acc: 0.7835\n",
      "Epoch 1350/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5194 - acc: 0.7510 - val_loss: 0.4832 - val_acc: 0.7756\n",
      "Epoch 1351/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4923 - acc: 0.7704 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 1352/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4827 - acc: 0.7607 - val_loss: 0.4795 - val_acc: 0.7835\n",
      "Epoch 1353/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4754 - acc: 0.7860 - val_loss: 0.4862 - val_acc: 0.7677\n",
      "Epoch 1354/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4992 - acc: 0.7451 - val_loss: 0.4842 - val_acc: 0.7638\n",
      "Epoch 1355/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4945 - acc: 0.7626 - val_loss: 0.4803 - val_acc: 0.7795\n",
      "Epoch 1356/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4936 - acc: 0.7412 - val_loss: 0.4822 - val_acc: 0.7717\n",
      "Epoch 1357/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4954 - acc: 0.7704 - val_loss: 0.4813 - val_acc: 0.7756\n",
      "Epoch 1358/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4866 - acc: 0.7432 - val_loss: 0.4829 - val_acc: 0.7756\n",
      "Epoch 1359/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 191us/step - loss: 0.4832 - acc: 0.7802 - val_loss: 0.4819 - val_acc: 0.7717\n",
      "Epoch 1360/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4999 - acc: 0.7529 - val_loss: 0.4837 - val_acc: 0.7756\n",
      "Epoch 1361/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5201 - acc: 0.7374 - val_loss: 0.4810 - val_acc: 0.7717\n",
      "Epoch 1362/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4937 - acc: 0.7588 - val_loss: 0.4831 - val_acc: 0.7717\n",
      "Epoch 1363/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5073 - acc: 0.7490 - val_loss: 0.4819 - val_acc: 0.7756\n",
      "Epoch 1364/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4873 - acc: 0.7471 - val_loss: 0.4810 - val_acc: 0.7717\n",
      "Epoch 1365/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4968 - acc: 0.7374 - val_loss: 0.4800 - val_acc: 0.7717\n",
      "Epoch 1366/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5131 - acc: 0.7471 - val_loss: 0.4809 - val_acc: 0.7717\n",
      "Epoch 1367/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4737 - acc: 0.7724 - val_loss: 0.4823 - val_acc: 0.7835\n",
      "Epoch 1368/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4952 - acc: 0.7588 - val_loss: 0.4855 - val_acc: 0.7835\n",
      "Epoch 1369/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5194 - acc: 0.7626 - val_loss: 0.4845 - val_acc: 0.7795\n",
      "Epoch 1370/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4874 - acc: 0.7568 - val_loss: 0.4814 - val_acc: 0.7795\n",
      "Epoch 1371/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5092 - acc: 0.7782 - val_loss: 0.4883 - val_acc: 0.7795\n",
      "Epoch 1372/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5076 - acc: 0.7665 - val_loss: 0.4889 - val_acc: 0.7835\n",
      "Epoch 1373/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5008 - acc: 0.7549 - val_loss: 0.4820 - val_acc: 0.7795\n",
      "Epoch 1374/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4901 - acc: 0.7607 - val_loss: 0.4809 - val_acc: 0.7795\n",
      "Epoch 1375/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5014 - acc: 0.7568 - val_loss: 0.4853 - val_acc: 0.7717\n",
      "Epoch 1376/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4921 - acc: 0.7510 - val_loss: 0.4822 - val_acc: 0.7756\n",
      "Epoch 1377/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4662 - acc: 0.7704 - val_loss: 0.4821 - val_acc: 0.7756\n",
      "Epoch 1378/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4918 - acc: 0.7607 - val_loss: 0.4823 - val_acc: 0.7756\n",
      "Epoch 1379/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4731 - acc: 0.7743 - val_loss: 0.4838 - val_acc: 0.7756\n",
      "Epoch 1380/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4990 - acc: 0.7685 - val_loss: 0.4829 - val_acc: 0.7795\n",
      "Epoch 1381/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4823 - acc: 0.7588 - val_loss: 0.4818 - val_acc: 0.7756\n",
      "Epoch 1382/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4956 - acc: 0.7607 - val_loss: 0.4817 - val_acc: 0.7756\n",
      "Epoch 1383/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4840 - acc: 0.7685 - val_loss: 0.4819 - val_acc: 0.7795\n",
      "Epoch 1384/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5093 - acc: 0.7451 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 1385/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5105 - acc: 0.7607 - val_loss: 0.4851 - val_acc: 0.7835\n",
      "Epoch 1386/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4944 - acc: 0.7626 - val_loss: 0.4829 - val_acc: 0.7756\n",
      "Epoch 1387/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5009 - acc: 0.7743 - val_loss: 0.4828 - val_acc: 0.7756\n",
      "Epoch 1388/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5183 - acc: 0.7685 - val_loss: 0.4847 - val_acc: 0.7756\n",
      "Epoch 1389/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4938 - acc: 0.7802 - val_loss: 0.4812 - val_acc: 0.7677\n",
      "Epoch 1390/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4686 - acc: 0.7451 - val_loss: 0.4831 - val_acc: 0.7756\n",
      "Epoch 1391/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4952 - acc: 0.7607 - val_loss: 0.4837 - val_acc: 0.7835\n",
      "Epoch 1392/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4716 - acc: 0.7743 - val_loss: 0.4808 - val_acc: 0.7835\n",
      "Epoch 1393/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4943 - acc: 0.7743 - val_loss: 0.4792 - val_acc: 0.7677\n",
      "Epoch 1394/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4818 - acc: 0.7665 - val_loss: 0.4799 - val_acc: 0.7717\n",
      "Epoch 1395/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4966 - acc: 0.7724 - val_loss: 0.4795 - val_acc: 0.7795\n",
      "Epoch 1396/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4920 - acc: 0.7763 - val_loss: 0.4793 - val_acc: 0.7835\n",
      "Epoch 1397/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4760 - acc: 0.7704 - val_loss: 0.4788 - val_acc: 0.7795\n",
      "Epoch 1398/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4986 - acc: 0.7393 - val_loss: 0.4781 - val_acc: 0.7795\n",
      "Epoch 1399/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4788 - acc: 0.7588 - val_loss: 0.4780 - val_acc: 0.7795\n",
      "Epoch 1400/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4997 - acc: 0.7743 - val_loss: 0.4822 - val_acc: 0.7835\n",
      "Epoch 1401/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5157 - acc: 0.7607 - val_loss: 0.4840 - val_acc: 0.7638\n",
      "Epoch 1402/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4863 - acc: 0.7665 - val_loss: 0.4804 - val_acc: 0.7638\n",
      "Epoch 1403/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5081 - acc: 0.7568 - val_loss: 0.4818 - val_acc: 0.7717\n",
      "Epoch 1404/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5080 - acc: 0.7607 - val_loss: 0.4796 - val_acc: 0.7717\n",
      "Epoch 1405/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5083 - acc: 0.7354 - val_loss: 0.4862 - val_acc: 0.7913\n",
      "Epoch 1406/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5022 - acc: 0.7510 - val_loss: 0.4997 - val_acc: 0.7795\n",
      "Epoch 1407/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5022 - acc: 0.7568 - val_loss: 0.4923 - val_acc: 0.7913\n",
      "Epoch 1408/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5367 - acc: 0.7451 - val_loss: 0.4883 - val_acc: 0.7913\n",
      "Epoch 1409/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4940 - acc: 0.7724 - val_loss: 0.4860 - val_acc: 0.7874\n",
      "Epoch 1410/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4973 - acc: 0.7451 - val_loss: 0.4848 - val_acc: 0.7953\n",
      "Epoch 1411/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5049 - acc: 0.7335 - val_loss: 0.4849 - val_acc: 0.7874\n",
      "Epoch 1412/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4950 - acc: 0.7490 - val_loss: 0.4848 - val_acc: 0.7795\n",
      "Epoch 1413/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5155 - acc: 0.7646 - val_loss: 0.4838 - val_acc: 0.7795\n",
      "Epoch 1414/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4990 - acc: 0.7821 - val_loss: 0.4818 - val_acc: 0.7795\n",
      "Epoch 1415/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4840 - acc: 0.7646 - val_loss: 0.4824 - val_acc: 0.7795\n",
      "Epoch 1416/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4922 - acc: 0.7607 - val_loss: 0.4868 - val_acc: 0.7598\n",
      "Epoch 1417/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4934 - acc: 0.7607 - val_loss: 0.4792 - val_acc: 0.7953\n",
      "Epoch 1418/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 192us/step - loss: 0.5003 - acc: 0.7646 - val_loss: 0.4832 - val_acc: 0.7795\n",
      "Epoch 1419/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5045 - acc: 0.7412 - val_loss: 0.4880 - val_acc: 0.7795\n",
      "Epoch 1420/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5068 - acc: 0.7296 - val_loss: 0.4800 - val_acc: 0.7835\n",
      "Epoch 1421/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5087 - acc: 0.7490 - val_loss: 0.4839 - val_acc: 0.7795\n",
      "Epoch 1422/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5154 - acc: 0.7432 - val_loss: 0.4806 - val_acc: 0.7756\n",
      "Epoch 1423/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5075 - acc: 0.7763 - val_loss: 0.4816 - val_acc: 0.7795\n",
      "Epoch 1424/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4882 - acc: 0.7665 - val_loss: 0.4860 - val_acc: 0.7795\n",
      "Epoch 1425/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4932 - acc: 0.7471 - val_loss: 0.4875 - val_acc: 0.7717\n",
      "Epoch 1426/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4933 - acc: 0.7646 - val_loss: 0.4846 - val_acc: 0.7756\n",
      "Epoch 1427/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4880 - acc: 0.7607 - val_loss: 0.4856 - val_acc: 0.7677\n",
      "Epoch 1428/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4993 - acc: 0.7451 - val_loss: 0.4805 - val_acc: 0.7795\n",
      "Epoch 1429/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5096 - acc: 0.7529 - val_loss: 0.4805 - val_acc: 0.7756\n",
      "Epoch 1430/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4805 - acc: 0.7626 - val_loss: 0.4837 - val_acc: 0.7795\n",
      "Epoch 1431/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5023 - acc: 0.7393 - val_loss: 0.4815 - val_acc: 0.7756\n",
      "Epoch 1432/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4906 - acc: 0.7724 - val_loss: 0.4794 - val_acc: 0.7795\n",
      "Epoch 1433/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4945 - acc: 0.7685 - val_loss: 0.4792 - val_acc: 0.7717\n",
      "Epoch 1434/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4944 - acc: 0.7549 - val_loss: 0.4804 - val_acc: 0.7717\n",
      "Epoch 1435/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5020 - acc: 0.7393 - val_loss: 0.4815 - val_acc: 0.7717\n",
      "Epoch 1436/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4752 - acc: 0.7685 - val_loss: 0.4819 - val_acc: 0.7795\n",
      "Epoch 1437/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4993 - acc: 0.7529 - val_loss: 0.4813 - val_acc: 0.7795\n",
      "Epoch 1438/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4898 - acc: 0.7432 - val_loss: 0.4807 - val_acc: 0.7756\n",
      "Epoch 1439/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4969 - acc: 0.7432 - val_loss: 0.4818 - val_acc: 0.7756\n",
      "Epoch 1440/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5023 - acc: 0.7529 - val_loss: 0.4835 - val_acc: 0.7835\n",
      "Epoch 1441/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5029 - acc: 0.7665 - val_loss: 0.4827 - val_acc: 0.7756\n",
      "Epoch 1442/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4880 - acc: 0.7568 - val_loss: 0.4828 - val_acc: 0.7717\n",
      "Epoch 1443/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5115 - acc: 0.7393 - val_loss: 0.4835 - val_acc: 0.7874\n",
      "Epoch 1444/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4910 - acc: 0.7743 - val_loss: 0.4845 - val_acc: 0.7795\n",
      "Epoch 1445/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4914 - acc: 0.7626 - val_loss: 0.4823 - val_acc: 0.7717\n",
      "Epoch 1446/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4790 - acc: 0.7588 - val_loss: 0.4897 - val_acc: 0.7795\n",
      "Epoch 1447/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4963 - acc: 0.7568 - val_loss: 0.4881 - val_acc: 0.7874\n",
      "Epoch 1448/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4841 - acc: 0.7821 - val_loss: 0.4850 - val_acc: 0.7717\n",
      "Epoch 1449/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4701 - acc: 0.7918 - val_loss: 0.4839 - val_acc: 0.7874\n",
      "Epoch 1450/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4748 - acc: 0.7840 - val_loss: 0.4883 - val_acc: 0.7717\n",
      "Epoch 1451/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5028 - acc: 0.7568 - val_loss: 0.4830 - val_acc: 0.7756\n",
      "Epoch 1452/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5086 - acc: 0.7374 - val_loss: 0.4846 - val_acc: 0.7795\n",
      "Epoch 1453/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4918 - acc: 0.7490 - val_loss: 0.4829 - val_acc: 0.7874\n",
      "Epoch 1454/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4900 - acc: 0.7665 - val_loss: 0.4858 - val_acc: 0.7638\n",
      "Epoch 1455/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4800 - acc: 0.7665 - val_loss: 0.4816 - val_acc: 0.7756\n",
      "Epoch 1456/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4978 - acc: 0.7374 - val_loss: 0.4821 - val_acc: 0.7717\n",
      "Epoch 1457/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5299 - acc: 0.7471 - val_loss: 0.4828 - val_acc: 0.7795\n",
      "Epoch 1458/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4900 - acc: 0.7529 - val_loss: 0.4831 - val_acc: 0.7795\n",
      "Epoch 1459/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4768 - acc: 0.7549 - val_loss: 0.4824 - val_acc: 0.7756\n",
      "Epoch 1460/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5074 - acc: 0.7646 - val_loss: 0.4833 - val_acc: 0.7756\n",
      "Epoch 1461/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4929 - acc: 0.7412 - val_loss: 0.4836 - val_acc: 0.7756\n",
      "Epoch 1462/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4708 - acc: 0.7626 - val_loss: 0.4862 - val_acc: 0.7677\n",
      "Epoch 1463/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4764 - acc: 0.7568 - val_loss: 0.4822 - val_acc: 0.7835\n",
      "Epoch 1464/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4994 - acc: 0.7646 - val_loss: 0.4815 - val_acc: 0.7756\n",
      "Epoch 1465/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5275 - acc: 0.7588 - val_loss: 0.4819 - val_acc: 0.7717\n",
      "Epoch 1466/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4655 - acc: 0.7588 - val_loss: 0.4843 - val_acc: 0.7795\n",
      "Epoch 1467/2000\n",
      "514/514 [==============================] - 0s 217us/step - loss: 0.4781 - acc: 0.7607 - val_loss: 0.4847 - val_acc: 0.7835\n",
      "Epoch 1468/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4732 - acc: 0.7549 - val_loss: 0.4846 - val_acc: 0.7874\n",
      "Epoch 1469/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5142 - acc: 0.7665 - val_loss: 0.4856 - val_acc: 0.7717\n",
      "Epoch 1470/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4897 - acc: 0.7510 - val_loss: 0.4845 - val_acc: 0.7717\n",
      "Epoch 1471/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5033 - acc: 0.7588 - val_loss: 0.4855 - val_acc: 0.7756\n",
      "Epoch 1472/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5020 - acc: 0.7549 - val_loss: 0.4848 - val_acc: 0.7756\n",
      "Epoch 1473/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4838 - acc: 0.7704 - val_loss: 0.4844 - val_acc: 0.7795\n",
      "Epoch 1474/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5036 - acc: 0.7510 - val_loss: 0.4859 - val_acc: 0.7795\n",
      "Epoch 1475/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4903 - acc: 0.7568 - val_loss: 0.4862 - val_acc: 0.7874\n",
      "Epoch 1476/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5054 - acc: 0.7315 - val_loss: 0.4862 - val_acc: 0.7795\n",
      "Epoch 1477/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 207us/step - loss: 0.5021 - acc: 0.7588 - val_loss: 0.4844 - val_acc: 0.7795\n",
      "Epoch 1478/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4937 - acc: 0.7432 - val_loss: 0.4866 - val_acc: 0.7756\n",
      "Epoch 1479/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5196 - acc: 0.7529 - val_loss: 0.4841 - val_acc: 0.7835\n",
      "Epoch 1480/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5009 - acc: 0.7704 - val_loss: 0.4873 - val_acc: 0.7756\n",
      "Epoch 1481/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4997 - acc: 0.7490 - val_loss: 0.4819 - val_acc: 0.7756\n",
      "Epoch 1482/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4876 - acc: 0.7743 - val_loss: 0.4844 - val_acc: 0.7795\n",
      "Epoch 1483/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5207 - acc: 0.7451 - val_loss: 0.4853 - val_acc: 0.7795\n",
      "Epoch 1484/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4731 - acc: 0.7724 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 1485/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5075 - acc: 0.7412 - val_loss: 0.4821 - val_acc: 0.7756\n",
      "Epoch 1486/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5127 - acc: 0.7471 - val_loss: 0.4852 - val_acc: 0.7835\n",
      "Epoch 1487/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4909 - acc: 0.7529 - val_loss: 0.4841 - val_acc: 0.7795\n",
      "Epoch 1488/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5164 - acc: 0.7490 - val_loss: 0.4900 - val_acc: 0.7835\n",
      "Epoch 1489/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5134 - acc: 0.7568 - val_loss: 0.4857 - val_acc: 0.7835\n",
      "Epoch 1490/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5229 - acc: 0.7490 - val_loss: 0.4843 - val_acc: 0.7756\n",
      "Epoch 1491/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4868 - acc: 0.7588 - val_loss: 0.4835 - val_acc: 0.7795\n",
      "Epoch 1492/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4933 - acc: 0.7588 - val_loss: 0.4846 - val_acc: 0.7756\n",
      "Epoch 1493/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4920 - acc: 0.7529 - val_loss: 0.4861 - val_acc: 0.7756\n",
      "Epoch 1494/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4832 - acc: 0.7626 - val_loss: 0.4867 - val_acc: 0.7756\n",
      "Epoch 1495/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4818 - acc: 0.7685 - val_loss: 0.4878 - val_acc: 0.7835\n",
      "Epoch 1496/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4938 - acc: 0.7432 - val_loss: 0.4875 - val_acc: 0.7795\n",
      "Epoch 1497/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4826 - acc: 0.7315 - val_loss: 0.4868 - val_acc: 0.7717\n",
      "Epoch 1498/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5012 - acc: 0.7510 - val_loss: 0.4863 - val_acc: 0.7717\n",
      "Epoch 1499/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5021 - acc: 0.7432 - val_loss: 0.4838 - val_acc: 0.7835\n",
      "Epoch 1500/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5033 - acc: 0.7471 - val_loss: 0.4851 - val_acc: 0.7756\n",
      "Epoch 1501/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5219 - acc: 0.7529 - val_loss: 0.4862 - val_acc: 0.7835\n",
      "Epoch 1502/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4769 - acc: 0.7665 - val_loss: 0.4866 - val_acc: 0.7717\n",
      "Epoch 1503/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4977 - acc: 0.7510 - val_loss: 0.4843 - val_acc: 0.7835\n",
      "Epoch 1504/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4970 - acc: 0.7568 - val_loss: 0.4862 - val_acc: 0.7795\n",
      "Epoch 1505/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4842 - acc: 0.7763 - val_loss: 0.4849 - val_acc: 0.7835\n",
      "Epoch 1506/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4945 - acc: 0.7607 - val_loss: 0.4881 - val_acc: 0.7835\n",
      "Epoch 1507/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5094 - acc: 0.7529 - val_loss: 0.4846 - val_acc: 0.7756\n",
      "Epoch 1508/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.5142 - acc: 0.7490 - val_loss: 0.4856 - val_acc: 0.7835\n",
      "Epoch 1509/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4874 - acc: 0.7393 - val_loss: 0.4843 - val_acc: 0.7717\n",
      "Epoch 1510/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5121 - acc: 0.7743 - val_loss: 0.4849 - val_acc: 0.7717\n",
      "Epoch 1511/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5023 - acc: 0.7549 - val_loss: 0.4836 - val_acc: 0.7795\n",
      "Epoch 1512/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5056 - acc: 0.7588 - val_loss: 0.4791 - val_acc: 0.7756\n",
      "Epoch 1513/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4704 - acc: 0.7568 - val_loss: 0.4818 - val_acc: 0.7795\n",
      "Epoch 1514/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4856 - acc: 0.7743 - val_loss: 0.4839 - val_acc: 0.7835\n",
      "Epoch 1515/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5051 - acc: 0.7685 - val_loss: 0.5065 - val_acc: 0.7559\n",
      "Epoch 1516/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5173 - acc: 0.7490 - val_loss: 0.4885 - val_acc: 0.7756\n",
      "Epoch 1517/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5209 - acc: 0.7510 - val_loss: 0.4905 - val_acc: 0.7756\n",
      "Epoch 1518/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5082 - acc: 0.7685 - val_loss: 0.4860 - val_acc: 0.7835\n",
      "Epoch 1519/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4914 - acc: 0.7918 - val_loss: 0.4849 - val_acc: 0.7835\n",
      "Epoch 1520/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4963 - acc: 0.7607 - val_loss: 0.4883 - val_acc: 0.7795\n",
      "Epoch 1521/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4857 - acc: 0.7704 - val_loss: 0.4803 - val_acc: 0.7874\n",
      "Epoch 1522/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4947 - acc: 0.7607 - val_loss: 0.4817 - val_acc: 0.7756\n",
      "Epoch 1523/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4916 - acc: 0.7588 - val_loss: 0.4797 - val_acc: 0.7795\n",
      "Epoch 1524/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5101 - acc: 0.7568 - val_loss: 0.4800 - val_acc: 0.7756\n",
      "Epoch 1525/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4886 - acc: 0.7529 - val_loss: 0.4781 - val_acc: 0.7835\n",
      "Epoch 1526/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4909 - acc: 0.7665 - val_loss: 0.4781 - val_acc: 0.7835\n",
      "Epoch 1527/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4896 - acc: 0.7626 - val_loss: 0.4853 - val_acc: 0.7756\n",
      "Epoch 1528/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5002 - acc: 0.7412 - val_loss: 0.4805 - val_acc: 0.7795\n",
      "Epoch 1529/2000\n",
      "514/514 [==============================] - 0s 219us/step - loss: 0.4802 - acc: 0.7451 - val_loss: 0.4812 - val_acc: 0.7835\n",
      "Epoch 1530/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5109 - acc: 0.7665 - val_loss: 0.4819 - val_acc: 0.7835\n",
      "Epoch 1531/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4802 - acc: 0.7451 - val_loss: 0.4796 - val_acc: 0.7795\n",
      "Epoch 1532/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5031 - acc: 0.7743 - val_loss: 0.4792 - val_acc: 0.7913\n",
      "Epoch 1533/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4626 - acc: 0.7782 - val_loss: 0.4795 - val_acc: 0.7835\n",
      "Epoch 1534/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4906 - acc: 0.7782 - val_loss: 0.4789 - val_acc: 0.7835\n",
      "Epoch 1535/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5024 - acc: 0.7724 - val_loss: 0.4834 - val_acc: 0.7677\n",
      "Epoch 1536/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 202us/step - loss: 0.5065 - acc: 0.7568 - val_loss: 0.5012 - val_acc: 0.7520\n",
      "Epoch 1537/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4961 - acc: 0.7354 - val_loss: 0.4837 - val_acc: 0.7874\n",
      "Epoch 1538/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4951 - acc: 0.7490 - val_loss: 0.4825 - val_acc: 0.7874\n",
      "Epoch 1539/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4826 - acc: 0.7724 - val_loss: 0.4832 - val_acc: 0.7717\n",
      "Epoch 1540/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4952 - acc: 0.7549 - val_loss: 0.4851 - val_acc: 0.7756\n",
      "Epoch 1541/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4888 - acc: 0.7588 - val_loss: 0.4860 - val_acc: 0.7795\n",
      "Epoch 1542/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4667 - acc: 0.7743 - val_loss: 0.4858 - val_acc: 0.7874\n",
      "Epoch 1543/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4834 - acc: 0.7665 - val_loss: 0.4812 - val_acc: 0.7835\n",
      "Epoch 1544/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4863 - acc: 0.7646 - val_loss: 0.4803 - val_acc: 0.7835\n",
      "Epoch 1545/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4932 - acc: 0.7665 - val_loss: 0.4808 - val_acc: 0.7835\n",
      "Epoch 1546/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4749 - acc: 0.7588 - val_loss: 0.4802 - val_acc: 0.7795\n",
      "Epoch 1547/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5075 - acc: 0.7549 - val_loss: 0.4812 - val_acc: 0.7756\n",
      "Epoch 1548/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4780 - acc: 0.7763 - val_loss: 0.4804 - val_acc: 0.7874\n",
      "Epoch 1549/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4880 - acc: 0.7704 - val_loss: 0.4836 - val_acc: 0.7677\n",
      "Epoch 1550/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4701 - acc: 0.7471 - val_loss: 0.4826 - val_acc: 0.7677\n",
      "Epoch 1551/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4687 - acc: 0.7743 - val_loss: 0.4804 - val_acc: 0.7717\n",
      "Epoch 1552/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5039 - acc: 0.7763 - val_loss: 0.4795 - val_acc: 0.7717\n",
      "Epoch 1553/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4987 - acc: 0.7510 - val_loss: 0.4820 - val_acc: 0.7874\n",
      "Epoch 1554/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4888 - acc: 0.7665 - val_loss: 0.4835 - val_acc: 0.7835\n",
      "Epoch 1555/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4974 - acc: 0.7685 - val_loss: 0.4844 - val_acc: 0.7677\n",
      "Epoch 1556/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4980 - acc: 0.7412 - val_loss: 0.4862 - val_acc: 0.7598\n",
      "Epoch 1557/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4949 - acc: 0.7568 - val_loss: 0.4869 - val_acc: 0.7598\n",
      "Epoch 1558/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4985 - acc: 0.7782 - val_loss: 0.4867 - val_acc: 0.7638\n",
      "Epoch 1559/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4693 - acc: 0.7782 - val_loss: 0.4844 - val_acc: 0.7795\n",
      "Epoch 1560/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4800 - acc: 0.7685 - val_loss: 0.4849 - val_acc: 0.7677\n",
      "Epoch 1561/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5028 - acc: 0.7451 - val_loss: 0.4884 - val_acc: 0.7559\n",
      "Epoch 1562/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4891 - acc: 0.7821 - val_loss: 0.4839 - val_acc: 0.7717\n",
      "Epoch 1563/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4954 - acc: 0.7724 - val_loss: 0.4885 - val_acc: 0.7598\n",
      "Epoch 1564/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4878 - acc: 0.7782 - val_loss: 0.4890 - val_acc: 0.7520\n",
      "Epoch 1565/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5237 - acc: 0.7665 - val_loss: 0.4807 - val_acc: 0.7835\n",
      "Epoch 1566/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4916 - acc: 0.7588 - val_loss: 0.4826 - val_acc: 0.7874\n",
      "Epoch 1567/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4888 - acc: 0.7743 - val_loss: 0.4847 - val_acc: 0.7874\n",
      "Epoch 1568/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4846 - acc: 0.7704 - val_loss: 0.4817 - val_acc: 0.7795\n",
      "Epoch 1569/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4805 - acc: 0.7568 - val_loss: 0.4873 - val_acc: 0.7677\n",
      "Epoch 1570/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4983 - acc: 0.7626 - val_loss: 0.4830 - val_acc: 0.7795\n",
      "Epoch 1571/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4961 - acc: 0.7471 - val_loss: 0.4823 - val_acc: 0.7913\n",
      "Epoch 1572/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4810 - acc: 0.7607 - val_loss: 0.4823 - val_acc: 0.7874\n",
      "Epoch 1573/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4810 - acc: 0.7782 - val_loss: 0.4827 - val_acc: 0.7756\n",
      "Epoch 1574/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5097 - acc: 0.7588 - val_loss: 0.4827 - val_acc: 0.7795\n",
      "Epoch 1575/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4902 - acc: 0.7724 - val_loss: 0.4857 - val_acc: 0.7835\n",
      "Epoch 1576/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4770 - acc: 0.7704 - val_loss: 0.4876 - val_acc: 0.7874\n",
      "Epoch 1577/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4588 - acc: 0.8035 - val_loss: 0.4846 - val_acc: 0.7795\n",
      "Epoch 1578/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4947 - acc: 0.7412 - val_loss: 0.4868 - val_acc: 0.7795\n",
      "Epoch 1579/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4876 - acc: 0.7626 - val_loss: 0.4855 - val_acc: 0.7874\n",
      "Epoch 1580/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4907 - acc: 0.7607 - val_loss: 0.4824 - val_acc: 0.7756\n",
      "Epoch 1581/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4831 - acc: 0.7724 - val_loss: 0.4824 - val_acc: 0.7874\n",
      "Epoch 1582/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5317 - acc: 0.7471 - val_loss: 0.4821 - val_acc: 0.7756\n",
      "Epoch 1583/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4859 - acc: 0.7626 - val_loss: 0.4834 - val_acc: 0.7756\n",
      "Epoch 1584/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.4841 - acc: 0.7879 - val_loss: 0.4842 - val_acc: 0.7835\n",
      "Epoch 1585/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4874 - acc: 0.7626 - val_loss: 0.4867 - val_acc: 0.7835\n",
      "Epoch 1586/2000\n",
      "514/514 [==============================] - 0s 229us/step - loss: 0.4947 - acc: 0.7665 - val_loss: 0.4835 - val_acc: 0.7795\n",
      "Epoch 1587/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4909 - acc: 0.7743 - val_loss: 0.4861 - val_acc: 0.7756\n",
      "Epoch 1588/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4785 - acc: 0.7626 - val_loss: 0.4823 - val_acc: 0.7913\n",
      "Epoch 1589/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4796 - acc: 0.7529 - val_loss: 0.4813 - val_acc: 0.7913\n",
      "Epoch 1590/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4822 - acc: 0.7782 - val_loss: 0.4824 - val_acc: 0.7913\n",
      "Epoch 1591/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5337 - acc: 0.7490 - val_loss: 0.4832 - val_acc: 0.7913\n",
      "Epoch 1592/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4965 - acc: 0.7529 - val_loss: 0.4838 - val_acc: 0.7835\n",
      "Epoch 1593/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4847 - acc: 0.7665 - val_loss: 0.4835 - val_acc: 0.7717\n",
      "Epoch 1594/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4828 - acc: 0.7607 - val_loss: 0.4830 - val_acc: 0.7756\n",
      "Epoch 1595/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 199us/step - loss: 0.4932 - acc: 0.7335 - val_loss: 0.4859 - val_acc: 0.7795\n",
      "Epoch 1596/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4869 - acc: 0.7704 - val_loss: 0.4904 - val_acc: 0.7756\n",
      "Epoch 1597/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4882 - acc: 0.7840 - val_loss: 0.4852 - val_acc: 0.7756\n",
      "Epoch 1598/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4911 - acc: 0.7665 - val_loss: 0.4856 - val_acc: 0.7874\n",
      "Epoch 1599/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4843 - acc: 0.7821 - val_loss: 0.4866 - val_acc: 0.7835\n",
      "Epoch 1600/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5076 - acc: 0.7607 - val_loss: 0.4887 - val_acc: 0.7835\n",
      "Epoch 1601/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4951 - acc: 0.7665 - val_loss: 0.4857 - val_acc: 0.7795\n",
      "Epoch 1602/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4863 - acc: 0.7529 - val_loss: 0.4853 - val_acc: 0.7795\n",
      "Epoch 1603/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4756 - acc: 0.7471 - val_loss: 0.4838 - val_acc: 0.7835\n",
      "Epoch 1604/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4706 - acc: 0.7763 - val_loss: 0.4865 - val_acc: 0.7677\n",
      "Epoch 1605/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5023 - acc: 0.7821 - val_loss: 0.4917 - val_acc: 0.7598\n",
      "Epoch 1606/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5340 - acc: 0.7743 - val_loss: 0.5089 - val_acc: 0.7598\n",
      "Epoch 1607/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4924 - acc: 0.7724 - val_loss: 0.4875 - val_acc: 0.7795\n",
      "Epoch 1608/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4946 - acc: 0.7646 - val_loss: 0.4887 - val_acc: 0.7717\n",
      "Epoch 1609/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5124 - acc: 0.7549 - val_loss: 0.4860 - val_acc: 0.7795\n",
      "Epoch 1610/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4857 - acc: 0.7568 - val_loss: 0.4842 - val_acc: 0.7756\n",
      "Epoch 1611/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5068 - acc: 0.7490 - val_loss: 0.4849 - val_acc: 0.7756\n",
      "Epoch 1612/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4677 - acc: 0.7685 - val_loss: 0.4839 - val_acc: 0.7756\n",
      "Epoch 1613/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4914 - acc: 0.7665 - val_loss: 0.4845 - val_acc: 0.7795\n",
      "Epoch 1614/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5031 - acc: 0.7510 - val_loss: 0.4844 - val_acc: 0.7717\n",
      "Epoch 1615/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4934 - acc: 0.7607 - val_loss: 0.4877 - val_acc: 0.7835\n",
      "Epoch 1616/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4879 - acc: 0.7860 - val_loss: 0.4869 - val_acc: 0.7756\n",
      "Epoch 1617/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5171 - acc: 0.7626 - val_loss: 0.4847 - val_acc: 0.7677\n",
      "Epoch 1618/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5032 - acc: 0.7471 - val_loss: 0.4846 - val_acc: 0.7756\n",
      "Epoch 1619/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4803 - acc: 0.7665 - val_loss: 0.4846 - val_acc: 0.7717\n",
      "Epoch 1620/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5145 - acc: 0.7607 - val_loss: 0.4835 - val_acc: 0.7795\n",
      "Epoch 1621/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4846 - acc: 0.7704 - val_loss: 0.4825 - val_acc: 0.7795\n",
      "Epoch 1622/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5061 - acc: 0.7412 - val_loss: 0.4830 - val_acc: 0.7795\n",
      "Epoch 1623/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5004 - acc: 0.7704 - val_loss: 0.4813 - val_acc: 0.7835\n",
      "Epoch 1624/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.5065 - acc: 0.7529 - val_loss: 0.4859 - val_acc: 0.7795\n",
      "Epoch 1625/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4934 - acc: 0.7704 - val_loss: 0.4840 - val_acc: 0.7835\n",
      "Epoch 1626/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4743 - acc: 0.7665 - val_loss: 0.4811 - val_acc: 0.7756\n",
      "Epoch 1627/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4864 - acc: 0.7704 - val_loss: 0.4823 - val_acc: 0.7835\n",
      "Epoch 1628/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4833 - acc: 0.7374 - val_loss: 0.4828 - val_acc: 0.7756\n",
      "Epoch 1629/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4985 - acc: 0.7763 - val_loss: 0.4832 - val_acc: 0.7795\n",
      "Epoch 1630/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5061 - acc: 0.7743 - val_loss: 0.4859 - val_acc: 0.7874\n",
      "Epoch 1631/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5034 - acc: 0.7860 - val_loss: 0.4856 - val_acc: 0.7756\n",
      "Epoch 1632/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4812 - acc: 0.7588 - val_loss: 0.4853 - val_acc: 0.7756\n",
      "Epoch 1633/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5080 - acc: 0.7626 - val_loss: 0.4817 - val_acc: 0.7756\n",
      "Epoch 1634/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4880 - acc: 0.7510 - val_loss: 0.4810 - val_acc: 0.7795\n",
      "Epoch 1635/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4877 - acc: 0.7665 - val_loss: 0.4857 - val_acc: 0.7795\n",
      "Epoch 1636/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4944 - acc: 0.7568 - val_loss: 0.4842 - val_acc: 0.7795\n",
      "Epoch 1637/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4758 - acc: 0.7704 - val_loss: 0.4831 - val_acc: 0.7756\n",
      "Epoch 1638/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4743 - acc: 0.7802 - val_loss: 0.4845 - val_acc: 0.7874\n",
      "Epoch 1639/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5105 - acc: 0.7782 - val_loss: 0.4881 - val_acc: 0.7874\n",
      "Epoch 1640/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4816 - acc: 0.7724 - val_loss: 0.4874 - val_acc: 0.7795\n",
      "Epoch 1641/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4878 - acc: 0.7490 - val_loss: 0.4851 - val_acc: 0.7874\n",
      "Epoch 1642/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4897 - acc: 0.7549 - val_loss: 0.4838 - val_acc: 0.7874\n",
      "Epoch 1643/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4954 - acc: 0.7490 - val_loss: 0.4871 - val_acc: 0.7835\n",
      "Epoch 1644/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4873 - acc: 0.7568 - val_loss: 0.4885 - val_acc: 0.7795\n",
      "Epoch 1645/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4961 - acc: 0.7821 - val_loss: 0.4873 - val_acc: 0.7835\n",
      "Epoch 1646/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4702 - acc: 0.7840 - val_loss: 0.4840 - val_acc: 0.7795\n",
      "Epoch 1647/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4720 - acc: 0.7743 - val_loss: 0.4843 - val_acc: 0.7795\n",
      "Epoch 1648/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4944 - acc: 0.7646 - val_loss: 0.4831 - val_acc: 0.7913\n",
      "Epoch 1649/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4722 - acc: 0.7860 - val_loss: 0.4886 - val_acc: 0.7638\n",
      "Epoch 1650/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5053 - acc: 0.7510 - val_loss: 0.4842 - val_acc: 0.7756\n",
      "Epoch 1651/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4658 - acc: 0.7899 - val_loss: 0.4839 - val_acc: 0.7756\n",
      "Epoch 1652/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4771 - acc: 0.7821 - val_loss: 0.4840 - val_acc: 0.7717\n",
      "Epoch 1653/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4896 - acc: 0.7451 - val_loss: 0.4831 - val_acc: 0.7795\n",
      "Epoch 1654/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 204us/step - loss: 0.5077 - acc: 0.7782 - val_loss: 0.4847 - val_acc: 0.7874\n",
      "Epoch 1655/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4699 - acc: 0.7510 - val_loss: 0.4861 - val_acc: 0.7795\n",
      "Epoch 1656/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5002 - acc: 0.7607 - val_loss: 0.4854 - val_acc: 0.7795\n",
      "Epoch 1657/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5031 - acc: 0.7529 - val_loss: 0.4857 - val_acc: 0.7795\n",
      "Epoch 1658/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4779 - acc: 0.7510 - val_loss: 0.4863 - val_acc: 0.7717\n",
      "Epoch 1659/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4993 - acc: 0.7607 - val_loss: 0.4865 - val_acc: 0.7795\n",
      "Epoch 1660/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4816 - acc: 0.7743 - val_loss: 0.4865 - val_acc: 0.7677\n",
      "Epoch 1661/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4948 - acc: 0.7821 - val_loss: 0.4843 - val_acc: 0.7913\n",
      "Epoch 1662/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4822 - acc: 0.7724 - val_loss: 0.4847 - val_acc: 0.7717\n",
      "Epoch 1663/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4956 - acc: 0.7646 - val_loss: 0.4842 - val_acc: 0.7756\n",
      "Epoch 1664/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.4796 - acc: 0.7704 - val_loss: 0.4880 - val_acc: 0.7756\n",
      "Epoch 1665/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4772 - acc: 0.7665 - val_loss: 0.4937 - val_acc: 0.7480\n",
      "Epoch 1666/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5088 - acc: 0.7840 - val_loss: 0.4877 - val_acc: 0.7795\n",
      "Epoch 1667/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5157 - acc: 0.7665 - val_loss: 0.4903 - val_acc: 0.7795\n",
      "Epoch 1668/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5132 - acc: 0.7646 - val_loss: 0.4913 - val_acc: 0.7795\n",
      "Epoch 1669/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4877 - acc: 0.7490 - val_loss: 0.4878 - val_acc: 0.7756\n",
      "Epoch 1670/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5081 - acc: 0.7412 - val_loss: 0.4886 - val_acc: 0.7874\n",
      "Epoch 1671/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4925 - acc: 0.7665 - val_loss: 0.4945 - val_acc: 0.7638\n",
      "Epoch 1672/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4918 - acc: 0.7529 - val_loss: 0.4920 - val_acc: 0.7795\n",
      "Epoch 1673/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4761 - acc: 0.7568 - val_loss: 0.4913 - val_acc: 0.7835\n",
      "Epoch 1674/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4792 - acc: 0.7549 - val_loss: 0.4876 - val_acc: 0.7835\n",
      "Epoch 1675/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4845 - acc: 0.7588 - val_loss: 0.4878 - val_acc: 0.7874\n",
      "Epoch 1676/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4790 - acc: 0.7802 - val_loss: 0.4887 - val_acc: 0.7874\n",
      "Epoch 1677/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5031 - acc: 0.7724 - val_loss: 0.4898 - val_acc: 0.7795\n",
      "Epoch 1678/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4828 - acc: 0.7568 - val_loss: 0.5000 - val_acc: 0.7559\n",
      "Epoch 1679/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5169 - acc: 0.7393 - val_loss: 0.4890 - val_acc: 0.7835\n",
      "Epoch 1680/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5051 - acc: 0.7490 - val_loss: 0.4920 - val_acc: 0.7835\n",
      "Epoch 1681/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4992 - acc: 0.7549 - val_loss: 0.4893 - val_acc: 0.7835\n",
      "Epoch 1682/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4945 - acc: 0.7549 - val_loss: 0.4858 - val_acc: 0.7795\n",
      "Epoch 1683/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4678 - acc: 0.7763 - val_loss: 0.4839 - val_acc: 0.7835\n",
      "Epoch 1684/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5110 - acc: 0.7646 - val_loss: 0.4846 - val_acc: 0.7795\n",
      "Epoch 1685/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4815 - acc: 0.7626 - val_loss: 0.4845 - val_acc: 0.7756\n",
      "Epoch 1686/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.4914 - acc: 0.7529 - val_loss: 0.4878 - val_acc: 0.7756\n",
      "Epoch 1687/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4910 - acc: 0.7335 - val_loss: 0.4875 - val_acc: 0.7756\n",
      "Epoch 1688/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4804 - acc: 0.7588 - val_loss: 0.4883 - val_acc: 0.7835\n",
      "Epoch 1689/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4986 - acc: 0.7626 - val_loss: 0.4877 - val_acc: 0.7756\n",
      "Epoch 1690/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4887 - acc: 0.7490 - val_loss: 0.4864 - val_acc: 0.7677\n",
      "Epoch 1691/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5178 - acc: 0.7237 - val_loss: 0.4863 - val_acc: 0.7756\n",
      "Epoch 1692/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4919 - acc: 0.7665 - val_loss: 0.4879 - val_acc: 0.7717\n",
      "Epoch 1693/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4819 - acc: 0.7568 - val_loss: 0.4849 - val_acc: 0.7717\n",
      "Epoch 1694/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4688 - acc: 0.7743 - val_loss: 0.4870 - val_acc: 0.7598\n",
      "Epoch 1695/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4843 - acc: 0.7704 - val_loss: 0.4825 - val_acc: 0.7717\n",
      "Epoch 1696/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4544 - acc: 0.7879 - val_loss: 0.4891 - val_acc: 0.7638\n",
      "Epoch 1697/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4814 - acc: 0.7646 - val_loss: 0.4866 - val_acc: 0.7559\n",
      "Epoch 1698/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4944 - acc: 0.7763 - val_loss: 0.4849 - val_acc: 0.7717\n",
      "Epoch 1699/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4973 - acc: 0.7471 - val_loss: 0.4851 - val_acc: 0.7756\n",
      "Epoch 1700/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4809 - acc: 0.7704 - val_loss: 0.4904 - val_acc: 0.7638\n",
      "Epoch 1701/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4864 - acc: 0.7451 - val_loss: 0.4892 - val_acc: 0.7638\n",
      "Epoch 1702/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4562 - acc: 0.7763 - val_loss: 0.4878 - val_acc: 0.7677\n",
      "Epoch 1703/2000\n",
      "514/514 [==============================] - 0s 221us/step - loss: 0.4884 - acc: 0.7510 - val_loss: 0.4878 - val_acc: 0.7638\n",
      "Epoch 1704/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4934 - acc: 0.7471 - val_loss: 0.4850 - val_acc: 0.7677\n",
      "Epoch 1705/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4761 - acc: 0.7802 - val_loss: 0.4887 - val_acc: 0.7638\n",
      "Epoch 1706/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4881 - acc: 0.7724 - val_loss: 0.4858 - val_acc: 0.7717\n",
      "Epoch 1707/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4901 - acc: 0.7704 - val_loss: 0.4816 - val_acc: 0.7756\n",
      "Epoch 1708/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4985 - acc: 0.7471 - val_loss: 0.4833 - val_acc: 0.7677\n",
      "Epoch 1709/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4920 - acc: 0.7665 - val_loss: 0.4838 - val_acc: 0.7756\n",
      "Epoch 1710/2000\n",
      "514/514 [==============================] - 0s 229us/step - loss: 0.4908 - acc: 0.7432 - val_loss: 0.4836 - val_acc: 0.7756\n",
      "Epoch 1711/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5255 - acc: 0.7510 - val_loss: 0.4832 - val_acc: 0.7677\n",
      "Epoch 1712/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4967 - acc: 0.7665 - val_loss: 0.4839 - val_acc: 0.7795\n",
      "Epoch 1713/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 192us/step - loss: 0.5020 - acc: 0.7704 - val_loss: 0.4841 - val_acc: 0.7717\n",
      "Epoch 1714/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5044 - acc: 0.7665 - val_loss: 0.4854 - val_acc: 0.7756\n",
      "Epoch 1715/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4783 - acc: 0.7840 - val_loss: 0.4856 - val_acc: 0.7677\n",
      "Epoch 1716/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4881 - acc: 0.7432 - val_loss: 0.4842 - val_acc: 0.7756\n",
      "Epoch 1717/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4845 - acc: 0.7510 - val_loss: 0.4885 - val_acc: 0.7795\n",
      "Epoch 1718/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4807 - acc: 0.7821 - val_loss: 0.4867 - val_acc: 0.7795\n",
      "Epoch 1719/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4871 - acc: 0.7685 - val_loss: 0.4860 - val_acc: 0.7756\n",
      "Epoch 1720/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4710 - acc: 0.7685 - val_loss: 0.4860 - val_acc: 0.7756\n",
      "Epoch 1721/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4988 - acc: 0.7802 - val_loss: 0.4855 - val_acc: 0.7835\n",
      "Epoch 1722/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4795 - acc: 0.7549 - val_loss: 0.4855 - val_acc: 0.7717\n",
      "Epoch 1723/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4818 - acc: 0.7490 - val_loss: 0.4899 - val_acc: 0.7598\n",
      "Epoch 1724/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4901 - acc: 0.7743 - val_loss: 0.4871 - val_acc: 0.7756\n",
      "Epoch 1725/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4762 - acc: 0.7704 - val_loss: 0.4859 - val_acc: 0.7756\n",
      "Epoch 1726/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4584 - acc: 0.7879 - val_loss: 0.4841 - val_acc: 0.7717\n",
      "Epoch 1727/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5051 - acc: 0.7432 - val_loss: 0.4863 - val_acc: 0.7874\n",
      "Epoch 1728/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4982 - acc: 0.7529 - val_loss: 0.4859 - val_acc: 0.7756\n",
      "Epoch 1729/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4905 - acc: 0.7335 - val_loss: 0.4866 - val_acc: 0.7638\n",
      "Epoch 1730/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4933 - acc: 0.7646 - val_loss: 0.4872 - val_acc: 0.7598\n",
      "Epoch 1731/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5195 - acc: 0.7665 - val_loss: 0.4858 - val_acc: 0.7717\n",
      "Epoch 1732/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4780 - acc: 0.7724 - val_loss: 0.4849 - val_acc: 0.7756\n",
      "Epoch 1733/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.4838 - acc: 0.7529 - val_loss: 0.4875 - val_acc: 0.7677\n",
      "Epoch 1734/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4825 - acc: 0.7685 - val_loss: 0.4836 - val_acc: 0.7756\n",
      "Epoch 1735/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4822 - acc: 0.7529 - val_loss: 0.4859 - val_acc: 0.7756\n",
      "Epoch 1736/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5028 - acc: 0.7704 - val_loss: 0.4872 - val_acc: 0.7835\n",
      "Epoch 1737/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4977 - acc: 0.7549 - val_loss: 0.4879 - val_acc: 0.7795\n",
      "Epoch 1738/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4889 - acc: 0.7646 - val_loss: 0.4857 - val_acc: 0.7756\n",
      "Epoch 1739/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4848 - acc: 0.7607 - val_loss: 0.4843 - val_acc: 0.7756\n",
      "Epoch 1740/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5211 - acc: 0.7412 - val_loss: 0.4840 - val_acc: 0.7795\n",
      "Epoch 1741/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4645 - acc: 0.7743 - val_loss: 0.4850 - val_acc: 0.7756\n",
      "Epoch 1742/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4794 - acc: 0.7724 - val_loss: 0.4885 - val_acc: 0.7874\n",
      "Epoch 1743/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4987 - acc: 0.7977 - val_loss: 0.4877 - val_acc: 0.7756\n",
      "Epoch 1744/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.5059 - acc: 0.7665 - val_loss: 0.4832 - val_acc: 0.7795\n",
      "Epoch 1745/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5014 - acc: 0.7704 - val_loss: 0.4847 - val_acc: 0.7795\n",
      "Epoch 1746/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4901 - acc: 0.7471 - val_loss: 0.4848 - val_acc: 0.7795\n",
      "Epoch 1747/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4717 - acc: 0.7626 - val_loss: 0.4877 - val_acc: 0.7756\n",
      "Epoch 1748/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4780 - acc: 0.7802 - val_loss: 0.4892 - val_acc: 0.7717\n",
      "Epoch 1749/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4884 - acc: 0.7665 - val_loss: 0.4873 - val_acc: 0.7756\n",
      "Epoch 1750/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5010 - acc: 0.7607 - val_loss: 0.4876 - val_acc: 0.7795\n",
      "Epoch 1751/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.4841 - acc: 0.7490 - val_loss: 0.4881 - val_acc: 0.7677\n",
      "Epoch 1752/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4936 - acc: 0.7549 - val_loss: 0.4875 - val_acc: 0.7638\n",
      "Epoch 1753/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4836 - acc: 0.7724 - val_loss: 0.4850 - val_acc: 0.7677\n",
      "Epoch 1754/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5308 - acc: 0.7412 - val_loss: 0.4852 - val_acc: 0.7835\n",
      "Epoch 1755/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.5011 - acc: 0.7665 - val_loss: 0.4854 - val_acc: 0.7874\n",
      "Epoch 1756/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.5129 - acc: 0.7588 - val_loss: 0.4850 - val_acc: 0.7913\n",
      "Epoch 1757/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5031 - acc: 0.7335 - val_loss: 0.4839 - val_acc: 0.7835\n",
      "Epoch 1758/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4808 - acc: 0.7724 - val_loss: 0.4845 - val_acc: 0.7795\n",
      "Epoch 1759/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5051 - acc: 0.7549 - val_loss: 0.4828 - val_acc: 0.7756\n",
      "Epoch 1760/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5110 - acc: 0.7549 - val_loss: 0.4806 - val_acc: 0.7677\n",
      "Epoch 1761/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.4890 - acc: 0.7724 - val_loss: 0.4949 - val_acc: 0.7756\n",
      "Epoch 1762/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4964 - acc: 0.7510 - val_loss: 0.4861 - val_acc: 0.7677\n",
      "Epoch 1763/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4916 - acc: 0.7646 - val_loss: 0.4802 - val_acc: 0.7795\n",
      "Epoch 1764/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.5130 - acc: 0.7276 - val_loss: 0.4815 - val_acc: 0.7835\n",
      "Epoch 1765/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4877 - acc: 0.7879 - val_loss: 0.4861 - val_acc: 0.7638\n",
      "Epoch 1766/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5020 - acc: 0.7626 - val_loss: 0.4810 - val_acc: 0.7677\n",
      "Epoch 1767/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4939 - acc: 0.7588 - val_loss: 0.4795 - val_acc: 0.7795\n",
      "Epoch 1768/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5087 - acc: 0.7626 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 1769/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4920 - acc: 0.7588 - val_loss: 0.4866 - val_acc: 0.7717\n",
      "Epoch 1770/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4947 - acc: 0.7549 - val_loss: 0.4850 - val_acc: 0.7717\n",
      "Epoch 1771/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.4860 - acc: 0.7510 - val_loss: 0.4848 - val_acc: 0.7835\n",
      "Epoch 1772/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 215us/step - loss: 0.4868 - acc: 0.7607 - val_loss: 0.4855 - val_acc: 0.7835\n",
      "Epoch 1773/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4968 - acc: 0.7646 - val_loss: 0.4851 - val_acc: 0.7795\n",
      "Epoch 1774/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.5086 - acc: 0.7626 - val_loss: 0.4864 - val_acc: 0.7835\n",
      "Epoch 1775/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4984 - acc: 0.7471 - val_loss: 0.4832 - val_acc: 0.7756\n",
      "Epoch 1776/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4976 - acc: 0.7588 - val_loss: 0.4841 - val_acc: 0.7717\n",
      "Epoch 1777/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5114 - acc: 0.7296 - val_loss: 0.4845 - val_acc: 0.7717\n",
      "Epoch 1778/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4854 - acc: 0.7432 - val_loss: 0.4845 - val_acc: 0.7795\n",
      "Epoch 1779/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4860 - acc: 0.7840 - val_loss: 0.4836 - val_acc: 0.7835\n",
      "Epoch 1780/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4782 - acc: 0.7782 - val_loss: 0.4840 - val_acc: 0.7756\n",
      "Epoch 1781/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4947 - acc: 0.7549 - val_loss: 0.4836 - val_acc: 0.7756\n",
      "Epoch 1782/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4905 - acc: 0.7549 - val_loss: 0.4854 - val_acc: 0.7756\n",
      "Epoch 1783/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.5184 - acc: 0.7471 - val_loss: 0.4848 - val_acc: 0.7795\n",
      "Epoch 1784/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4829 - acc: 0.7568 - val_loss: 0.4826 - val_acc: 0.7835\n",
      "Epoch 1785/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5024 - acc: 0.7607 - val_loss: 0.4948 - val_acc: 0.7717\n",
      "Epoch 1786/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5058 - acc: 0.7549 - val_loss: 0.4907 - val_acc: 0.7756\n",
      "Epoch 1787/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5020 - acc: 0.7743 - val_loss: 0.4947 - val_acc: 0.7677\n",
      "Epoch 1788/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4965 - acc: 0.7510 - val_loss: 0.4919 - val_acc: 0.7638\n",
      "Epoch 1789/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5286 - acc: 0.7510 - val_loss: 0.4847 - val_acc: 0.7795\n",
      "Epoch 1790/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5193 - acc: 0.7335 - val_loss: 0.4933 - val_acc: 0.7795\n",
      "Epoch 1791/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5053 - acc: 0.7646 - val_loss: 0.4832 - val_acc: 0.7677\n",
      "Epoch 1792/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5101 - acc: 0.7782 - val_loss: 0.4809 - val_acc: 0.7638\n",
      "Epoch 1793/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5193 - acc: 0.7432 - val_loss: 0.4848 - val_acc: 0.7756\n",
      "Epoch 1794/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4770 - acc: 0.7665 - val_loss: 0.4863 - val_acc: 0.7756\n",
      "Epoch 1795/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5157 - acc: 0.7626 - val_loss: 0.4873 - val_acc: 0.7717\n",
      "Epoch 1796/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.5083 - acc: 0.7529 - val_loss: 0.4852 - val_acc: 0.7717\n",
      "Epoch 1797/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5081 - acc: 0.7568 - val_loss: 0.4871 - val_acc: 0.7717\n",
      "Epoch 1798/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5097 - acc: 0.7374 - val_loss: 0.4865 - val_acc: 0.7795\n",
      "Epoch 1799/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4982 - acc: 0.7276 - val_loss: 0.4837 - val_acc: 0.7756\n",
      "Epoch 1800/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4832 - acc: 0.7685 - val_loss: 0.4853 - val_acc: 0.7756\n",
      "Epoch 1801/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4899 - acc: 0.7646 - val_loss: 0.4861 - val_acc: 0.7756\n",
      "Epoch 1802/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4810 - acc: 0.7510 - val_loss: 0.4853 - val_acc: 0.7756\n",
      "Epoch 1803/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.4972 - acc: 0.7626 - val_loss: 0.4956 - val_acc: 0.7598\n",
      "Epoch 1804/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5035 - acc: 0.7588 - val_loss: 0.4971 - val_acc: 0.7835\n",
      "Epoch 1805/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4901 - acc: 0.7393 - val_loss: 0.4882 - val_acc: 0.7874\n",
      "Epoch 1806/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5009 - acc: 0.7510 - val_loss: 0.4891 - val_acc: 0.7756\n",
      "Epoch 1807/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4661 - acc: 0.7743 - val_loss: 0.4859 - val_acc: 0.7677\n",
      "Epoch 1808/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5118 - acc: 0.7549 - val_loss: 0.4863 - val_acc: 0.7756\n",
      "Epoch 1809/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4895 - acc: 0.7782 - val_loss: 0.4880 - val_acc: 0.7756\n",
      "Epoch 1810/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4858 - acc: 0.7665 - val_loss: 0.4865 - val_acc: 0.7795\n",
      "Epoch 1811/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4828 - acc: 0.7782 - val_loss: 0.4849 - val_acc: 0.7756\n",
      "Epoch 1812/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4783 - acc: 0.7626 - val_loss: 0.4859 - val_acc: 0.7756\n",
      "Epoch 1813/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4707 - acc: 0.7782 - val_loss: 0.4883 - val_acc: 0.7795\n",
      "Epoch 1814/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4780 - acc: 0.7704 - val_loss: 0.4868 - val_acc: 0.7756\n",
      "Epoch 1815/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4693 - acc: 0.7665 - val_loss: 0.4850 - val_acc: 0.7756\n",
      "Epoch 1816/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5075 - acc: 0.7646 - val_loss: 0.4872 - val_acc: 0.7756\n",
      "Epoch 1817/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.5008 - acc: 0.7588 - val_loss: 0.4861 - val_acc: 0.7717\n",
      "Epoch 1818/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4693 - acc: 0.7665 - val_loss: 0.4833 - val_acc: 0.7717\n",
      "Epoch 1819/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4837 - acc: 0.7607 - val_loss: 0.4851 - val_acc: 0.7677\n",
      "Epoch 1820/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4810 - acc: 0.7724 - val_loss: 0.4882 - val_acc: 0.7835\n",
      "Epoch 1821/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4961 - acc: 0.7665 - val_loss: 0.4848 - val_acc: 0.7717\n",
      "Epoch 1822/2000\n",
      "514/514 [==============================] - 0s 184us/step - loss: 0.4716 - acc: 0.7665 - val_loss: 0.4862 - val_acc: 0.7795\n",
      "Epoch 1823/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4913 - acc: 0.7821 - val_loss: 0.5187 - val_acc: 0.7520\n",
      "Epoch 1824/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.5184 - acc: 0.7374 - val_loss: 0.4955 - val_acc: 0.7559\n",
      "Epoch 1825/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4989 - acc: 0.7685 - val_loss: 0.4921 - val_acc: 0.7874\n",
      "Epoch 1826/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4909 - acc: 0.7646 - val_loss: 0.4954 - val_acc: 0.7480\n",
      "Epoch 1827/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.5145 - acc: 0.7490 - val_loss: 0.4941 - val_acc: 0.7638\n",
      "Epoch 1828/2000\n",
      "514/514 [==============================] - 0s 186us/step - loss: 0.4872 - acc: 0.7821 - val_loss: 0.4914 - val_acc: 0.7874\n",
      "Epoch 1829/2000\n",
      "514/514 [==============================] - 0s 183us/step - loss: 0.4815 - acc: 0.7704 - val_loss: 0.4901 - val_acc: 0.7835\n",
      "Epoch 1830/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4871 - acc: 0.7412 - val_loss: 0.4895 - val_acc: 0.7717\n",
      "Epoch 1831/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 211us/step - loss: 0.4849 - acc: 0.7782 - val_loss: 0.4953 - val_acc: 0.7638\n",
      "Epoch 1832/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5027 - acc: 0.7471 - val_loss: 0.4921 - val_acc: 0.7598\n",
      "Epoch 1833/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5069 - acc: 0.7704 - val_loss: 0.4918 - val_acc: 0.7638\n",
      "Epoch 1834/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5013 - acc: 0.7490 - val_loss: 0.4887 - val_acc: 0.7717\n",
      "Epoch 1835/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4885 - acc: 0.7646 - val_loss: 0.4873 - val_acc: 0.7677\n",
      "Epoch 1836/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4843 - acc: 0.7529 - val_loss: 0.4878 - val_acc: 0.7677\n",
      "Epoch 1837/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4970 - acc: 0.7588 - val_loss: 0.4863 - val_acc: 0.7717\n",
      "Epoch 1838/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4808 - acc: 0.7432 - val_loss: 0.4846 - val_acc: 0.7756\n",
      "Epoch 1839/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4940 - acc: 0.7568 - val_loss: 0.4857 - val_acc: 0.7717\n",
      "Epoch 1840/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5035 - acc: 0.7549 - val_loss: 0.4853 - val_acc: 0.7598\n",
      "Epoch 1841/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5025 - acc: 0.7626 - val_loss: 0.4849 - val_acc: 0.7717\n",
      "Epoch 1842/2000\n",
      "514/514 [==============================] - 0s 187us/step - loss: 0.5007 - acc: 0.7646 - val_loss: 0.4868 - val_acc: 0.7717\n",
      "Epoch 1843/2000\n",
      "514/514 [==============================] - 0s 231us/step - loss: 0.4747 - acc: 0.7568 - val_loss: 0.4831 - val_acc: 0.7717\n",
      "Epoch 1844/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4775 - acc: 0.7626 - val_loss: 0.4848 - val_acc: 0.7677\n",
      "Epoch 1845/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.5098 - acc: 0.7665 - val_loss: 0.4890 - val_acc: 0.7717\n",
      "Epoch 1846/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.4793 - acc: 0.7743 - val_loss: 0.4869 - val_acc: 0.7756\n",
      "Epoch 1847/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4988 - acc: 0.7607 - val_loss: 0.4871 - val_acc: 0.7717\n",
      "Epoch 1848/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4836 - acc: 0.7685 - val_loss: 0.4878 - val_acc: 0.7559\n",
      "Epoch 1849/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5151 - acc: 0.7549 - val_loss: 0.4862 - val_acc: 0.7717\n",
      "Epoch 1850/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4732 - acc: 0.7743 - val_loss: 0.4843 - val_acc: 0.7756\n",
      "Epoch 1851/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5030 - acc: 0.7549 - val_loss: 0.4848 - val_acc: 0.7677\n",
      "Epoch 1852/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5105 - acc: 0.7704 - val_loss: 0.4851 - val_acc: 0.7717\n",
      "Epoch 1853/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5055 - acc: 0.7568 - val_loss: 0.4823 - val_acc: 0.7795\n",
      "Epoch 1854/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5073 - acc: 0.7490 - val_loss: 0.4819 - val_acc: 0.7717\n",
      "Epoch 1855/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5004 - acc: 0.7471 - val_loss: 0.4815 - val_acc: 0.7677\n",
      "Epoch 1856/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4946 - acc: 0.7490 - val_loss: 0.4884 - val_acc: 0.7874\n",
      "Epoch 1857/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.4870 - acc: 0.7471 - val_loss: 0.4865 - val_acc: 0.7717\n",
      "Epoch 1858/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4978 - acc: 0.7626 - val_loss: 0.4852 - val_acc: 0.7756\n",
      "Epoch 1859/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5160 - acc: 0.7374 - val_loss: 0.4851 - val_acc: 0.7795\n",
      "Epoch 1860/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5154 - acc: 0.7471 - val_loss: 0.4864 - val_acc: 0.7717\n",
      "Epoch 1861/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4699 - acc: 0.7724 - val_loss: 0.4819 - val_acc: 0.7717\n",
      "Epoch 1862/2000\n",
      "514/514 [==============================] - 0s 203us/step - loss: 0.5085 - acc: 0.7665 - val_loss: 0.4816 - val_acc: 0.7756\n",
      "Epoch 1863/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4947 - acc: 0.7568 - val_loss: 0.4825 - val_acc: 0.7795\n",
      "Epoch 1864/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.4783 - acc: 0.7704 - val_loss: 0.4816 - val_acc: 0.7756\n",
      "Epoch 1865/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4817 - acc: 0.7763 - val_loss: 0.4870 - val_acc: 0.7795\n",
      "Epoch 1866/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4613 - acc: 0.7802 - val_loss: 0.4862 - val_acc: 0.7835\n",
      "Epoch 1867/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4952 - acc: 0.7549 - val_loss: 0.4884 - val_acc: 0.7795\n",
      "Epoch 1868/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4941 - acc: 0.7412 - val_loss: 0.4867 - val_acc: 0.7756\n",
      "Epoch 1869/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4869 - acc: 0.7490 - val_loss: 0.4866 - val_acc: 0.7717\n",
      "Epoch 1870/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4994 - acc: 0.7899 - val_loss: 0.4874 - val_acc: 0.7756\n",
      "Epoch 1871/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4830 - acc: 0.7704 - val_loss: 0.4876 - val_acc: 0.7756\n",
      "Epoch 1872/2000\n",
      "514/514 [==============================] - 0s 205us/step - loss: 0.4999 - acc: 0.7704 - val_loss: 0.4913 - val_acc: 0.7598\n",
      "Epoch 1873/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4910 - acc: 0.7665 - val_loss: 0.4875 - val_acc: 0.7677\n",
      "Epoch 1874/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4772 - acc: 0.7918 - val_loss: 0.4874 - val_acc: 0.7598\n",
      "Epoch 1875/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4837 - acc: 0.7471 - val_loss: 0.4834 - val_acc: 0.7835\n",
      "Epoch 1876/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4735 - acc: 0.7529 - val_loss: 0.4826 - val_acc: 0.7717\n",
      "Epoch 1877/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4876 - acc: 0.7607 - val_loss: 0.4832 - val_acc: 0.7835\n",
      "Epoch 1878/2000\n",
      "514/514 [==============================] - 0s 224us/step - loss: 0.4857 - acc: 0.7763 - val_loss: 0.4864 - val_acc: 0.7717\n",
      "Epoch 1879/2000\n",
      "514/514 [==============================] - 0s 245us/step - loss: 0.5012 - acc: 0.7607 - val_loss: 0.4900 - val_acc: 0.7756\n",
      "Epoch 1880/2000\n",
      "514/514 [==============================] - 0s 243us/step - loss: 0.4860 - acc: 0.7646 - val_loss: 0.4852 - val_acc: 0.7717\n",
      "Epoch 1881/2000\n",
      "514/514 [==============================] - 0s 215us/step - loss: 0.4909 - acc: 0.7529 - val_loss: 0.4863 - val_acc: 0.7677\n",
      "Epoch 1882/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.5022 - acc: 0.7665 - val_loss: 0.4913 - val_acc: 0.7559\n",
      "Epoch 1883/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.4846 - acc: 0.7646 - val_loss: 0.4923 - val_acc: 0.7520\n",
      "Epoch 1884/2000\n",
      "514/514 [==============================] - 0s 209us/step - loss: 0.4727 - acc: 0.7665 - val_loss: 0.4825 - val_acc: 0.7756\n",
      "Epoch 1885/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.4908 - acc: 0.7588 - val_loss: 0.4840 - val_acc: 0.7756\n",
      "Epoch 1886/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.5222 - acc: 0.7743 - val_loss: 0.4879 - val_acc: 0.7677\n",
      "Epoch 1887/2000\n",
      "514/514 [==============================] - 0s 204us/step - loss: 0.5183 - acc: 0.7549 - val_loss: 0.4826 - val_acc: 0.7756\n",
      "Epoch 1888/2000\n",
      "514/514 [==============================] - 0s 211us/step - loss: 0.5021 - acc: 0.7451 - val_loss: 0.4822 - val_acc: 0.7874\n",
      "Epoch 1889/2000\n",
      "514/514 [==============================] - 0s 213us/step - loss: 0.4887 - acc: 0.7626 - val_loss: 0.4833 - val_acc: 0.7756\n",
      "Epoch 1890/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 208us/step - loss: 0.4827 - acc: 0.7490 - val_loss: 0.4829 - val_acc: 0.7756\n",
      "Epoch 1891/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.4889 - acc: 0.7704 - val_loss: 0.4868 - val_acc: 0.7677\n",
      "Epoch 1892/2000\n",
      "514/514 [==============================] - 0s 199us/step - loss: 0.5227 - acc: 0.7549 - val_loss: 0.4858 - val_acc: 0.7756\n",
      "Epoch 1893/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4994 - acc: 0.7510 - val_loss: 0.4848 - val_acc: 0.7913\n",
      "Epoch 1894/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4884 - acc: 0.7354 - val_loss: 0.4838 - val_acc: 0.7874\n",
      "Epoch 1895/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4824 - acc: 0.7665 - val_loss: 0.4850 - val_acc: 0.7756\n",
      "Epoch 1896/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4756 - acc: 0.7860 - val_loss: 0.4837 - val_acc: 0.7717\n",
      "Epoch 1897/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5190 - acc: 0.7704 - val_loss: 0.4845 - val_acc: 0.7756\n",
      "Epoch 1898/2000\n",
      "514/514 [==============================] - 0s 221us/step - loss: 0.4696 - acc: 0.7763 - val_loss: 0.4833 - val_acc: 0.7795\n",
      "Epoch 1899/2000\n",
      "514/514 [==============================] - 0s 193us/step - loss: 0.4810 - acc: 0.7665 - val_loss: 0.4891 - val_acc: 0.7559\n",
      "Epoch 1900/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.5193 - acc: 0.7393 - val_loss: 0.4947 - val_acc: 0.7677\n",
      "Epoch 1901/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.5057 - acc: 0.7724 - val_loss: 0.4788 - val_acc: 0.7717\n",
      "Epoch 1902/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4899 - acc: 0.7724 - val_loss: 0.4824 - val_acc: 0.7795\n",
      "Epoch 1903/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.5090 - acc: 0.7607 - val_loss: 0.4849 - val_acc: 0.7717\n",
      "Epoch 1904/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.5048 - acc: 0.7685 - val_loss: 0.4829 - val_acc: 0.7756\n",
      "Epoch 1905/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4812 - acc: 0.7879 - val_loss: 0.4802 - val_acc: 0.7756\n",
      "Epoch 1906/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4911 - acc: 0.7685 - val_loss: 0.4797 - val_acc: 0.7717\n",
      "Epoch 1907/2000\n",
      "514/514 [==============================] - 0s 201us/step - loss: 0.4917 - acc: 0.7607 - val_loss: 0.4821 - val_acc: 0.7874\n",
      "Epoch 1908/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5087 - acc: 0.7743 - val_loss: 0.4877 - val_acc: 0.7677\n",
      "Epoch 1909/2000\n",
      "514/514 [==============================] - 0s 188us/step - loss: 0.4927 - acc: 0.7646 - val_loss: 0.4840 - val_acc: 0.7756\n",
      "Epoch 1910/2000\n",
      "514/514 [==============================] - 0s 195us/step - loss: 0.5155 - acc: 0.7432 - val_loss: 0.4817 - val_acc: 0.7835\n",
      "Epoch 1911/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5026 - acc: 0.7315 - val_loss: 0.4830 - val_acc: 0.7756\n",
      "Epoch 1912/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.4871 - acc: 0.7763 - val_loss: 0.4826 - val_acc: 0.7756\n",
      "Epoch 1913/2000\n",
      "514/514 [==============================] - 0s 198us/step - loss: 0.5002 - acc: 0.7588 - val_loss: 0.4861 - val_acc: 0.7874\n",
      "Epoch 1914/2000\n",
      "514/514 [==============================] - 0s 185us/step - loss: 0.4863 - acc: 0.7724 - val_loss: 0.4844 - val_acc: 0.7795\n",
      "Epoch 1915/2000\n",
      "514/514 [==============================] - 0s 191us/step - loss: 0.4833 - acc: 0.7782 - val_loss: 0.4820 - val_acc: 0.7756\n",
      "Epoch 1916/2000\n",
      "514/514 [==============================] - 0s 192us/step - loss: 0.4814 - acc: 0.7743 - val_loss: 0.4836 - val_acc: 0.7835\n",
      "Epoch 1917/2000\n",
      "514/514 [==============================] - 0s 189us/step - loss: 0.5057 - acc: 0.7451 - val_loss: 0.4822 - val_acc: 0.7677\n",
      "Epoch 1918/2000\n",
      "514/514 [==============================] - 0s 190us/step - loss: 0.5046 - acc: 0.7549 - val_loss: 0.4834 - val_acc: 0.7835\n",
      "Epoch 1919/2000\n",
      "514/514 [==============================] - 0s 196us/step - loss: 0.4803 - acc: 0.7588 - val_loss: 0.4833 - val_acc: 0.7795\n",
      "Epoch 1920/2000\n",
      "514/514 [==============================] - 0s 207us/step - loss: 0.4819 - acc: 0.7626 - val_loss: 0.4825 - val_acc: 0.7795\n",
      "Epoch 1921/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.5033 - acc: 0.7510 - val_loss: 0.4863 - val_acc: 0.7992\n",
      "Epoch 1922/2000\n",
      "514/514 [==============================] - 0s 200us/step - loss: 0.4729 - acc: 0.7860 - val_loss: 0.4841 - val_acc: 0.7795\n",
      "Epoch 1923/2000\n",
      "514/514 [==============================] - 0s 197us/step - loss: 0.4842 - acc: 0.7685 - val_loss: 0.4810 - val_acc: 0.7835\n",
      "Epoch 1924/2000\n",
      "514/514 [==============================] - 0s 194us/step - loss: 0.4918 - acc: 0.7743 - val_loss: 0.4820 - val_acc: 0.7874\n",
      "Epoch 1925/2000\n",
      "514/514 [==============================] - 0s 202us/step - loss: 0.4949 - acc: 0.7568 - val_loss: 0.4825 - val_acc: 0.7756\n",
      "Epoch 1926/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4623 - acc: 0.7665 - val_loss: 0.4879 - val_acc: 0.7717\n",
      "Epoch 1927/2000\n",
      "514/514 [==============================] - 0s 224us/step - loss: 0.5136 - acc: 0.7607 - val_loss: 0.4855 - val_acc: 0.7835\n",
      "Epoch 1928/2000\n",
      "514/514 [==============================] - 0s 235us/step - loss: 0.4901 - acc: 0.7802 - val_loss: 0.4878 - val_acc: 0.7913\n",
      "Epoch 1929/2000\n",
      "514/514 [==============================] - 0s 238us/step - loss: 0.4796 - acc: 0.7782 - val_loss: 0.4883 - val_acc: 0.7717\n",
      "Epoch 1930/2000\n",
      "514/514 [==============================] - 0s 244us/step - loss: 0.5011 - acc: 0.7724 - val_loss: 0.4900 - val_acc: 0.7598\n",
      "Epoch 1931/2000\n",
      "514/514 [==============================] - 0s 234us/step - loss: 0.4849 - acc: 0.7879 - val_loss: 0.4851 - val_acc: 0.7913\n",
      "Epoch 1932/2000\n",
      "514/514 [==============================] - 0s 258us/step - loss: 0.4917 - acc: 0.7665 - val_loss: 0.4875 - val_acc: 0.7756\n",
      "Epoch 1933/2000\n",
      "514/514 [==============================] - 0s 255us/step - loss: 0.4948 - acc: 0.7665 - val_loss: 0.4836 - val_acc: 0.7717\n",
      "Epoch 1934/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.4862 - acc: 0.7879 - val_loss: 0.4826 - val_acc: 0.7756\n",
      "Epoch 1935/2000\n",
      "514/514 [==============================] - 0s 263us/step - loss: 0.4948 - acc: 0.7607 - val_loss: 0.4857 - val_acc: 0.7756\n",
      "Epoch 1936/2000\n",
      "514/514 [==============================] - 0s 223us/step - loss: 0.4705 - acc: 0.7802 - val_loss: 0.4862 - val_acc: 0.7717\n",
      "Epoch 1937/2000\n",
      "514/514 [==============================] - 0s 224us/step - loss: 0.4986 - acc: 0.7646 - val_loss: 0.4833 - val_acc: 0.7835\n",
      "Epoch 1938/2000\n",
      "514/514 [==============================] - 0s 222us/step - loss: 0.4842 - acc: 0.7724 - val_loss: 0.4811 - val_acc: 0.7717\n",
      "Epoch 1939/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4882 - acc: 0.7821 - val_loss: 0.4835 - val_acc: 0.7756\n",
      "Epoch 1940/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.4728 - acc: 0.7763 - val_loss: 0.4860 - val_acc: 0.7638\n",
      "Epoch 1941/2000\n",
      "514/514 [==============================] - 0s 220us/step - loss: 0.5029 - acc: 0.7490 - val_loss: 0.4808 - val_acc: 0.7795\n",
      "Epoch 1942/2000\n",
      "514/514 [==============================] - 0s 218us/step - loss: 0.4980 - acc: 0.7588 - val_loss: 0.4856 - val_acc: 0.7717\n",
      "Epoch 1943/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.4907 - acc: 0.7685 - val_loss: 0.4844 - val_acc: 0.7756\n",
      "Epoch 1944/2000\n",
      "514/514 [==============================] - 0s 230us/step - loss: 0.4730 - acc: 0.7549 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 1945/2000\n",
      "514/514 [==============================] - 0s 274us/step - loss: 0.4728 - acc: 0.7685 - val_loss: 0.4827 - val_acc: 0.7717\n",
      "Epoch 1946/2000\n",
      "514/514 [==============================] - 0s 250us/step - loss: 0.4960 - acc: 0.7568 - val_loss: 0.4838 - val_acc: 0.7756\n",
      "Epoch 1947/2000\n",
      "514/514 [==============================] - 0s 231us/step - loss: 0.5127 - acc: 0.7549 - val_loss: 0.4889 - val_acc: 0.7795\n",
      "Epoch 1948/2000\n",
      "514/514 [==============================] - 0s 239us/step - loss: 0.4696 - acc: 0.7685 - val_loss: 0.4810 - val_acc: 0.7756\n",
      "Epoch 1949/2000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "514/514 [==============================] - 0s 213us/step - loss: 0.5008 - acc: 0.7763 - val_loss: 0.4805 - val_acc: 0.7756\n",
      "Epoch 1950/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4975 - acc: 0.7685 - val_loss: 0.4835 - val_acc: 0.7835\n",
      "Epoch 1951/2000\n",
      "514/514 [==============================] - 0s 240us/step - loss: 0.5034 - acc: 0.7724 - val_loss: 0.4836 - val_acc: 0.7835\n",
      "Epoch 1952/2000\n",
      "514/514 [==============================] - 0s 235us/step - loss: 0.5244 - acc: 0.7432 - val_loss: 0.4856 - val_acc: 0.7756\n",
      "Epoch 1953/2000\n",
      "514/514 [==============================] - 0s 223us/step - loss: 0.4925 - acc: 0.7743 - val_loss: 0.4821 - val_acc: 0.7795\n",
      "Epoch 1954/2000\n",
      "514/514 [==============================] - 0s 236us/step - loss: 0.4813 - acc: 0.7763 - val_loss: 0.4853 - val_acc: 0.7835\n",
      "Epoch 1955/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.4845 - acc: 0.7568 - val_loss: 0.4813 - val_acc: 0.7756\n",
      "Epoch 1956/2000\n",
      "514/514 [==============================] - 0s 236us/step - loss: 0.4960 - acc: 0.7626 - val_loss: 0.4858 - val_acc: 0.7756\n",
      "Epoch 1957/2000\n",
      "514/514 [==============================] - 0s 237us/step - loss: 0.4998 - acc: 0.7432 - val_loss: 0.4814 - val_acc: 0.7756\n",
      "Epoch 1958/2000\n",
      "514/514 [==============================] - 0s 206us/step - loss: 0.4845 - acc: 0.7802 - val_loss: 0.4846 - val_acc: 0.7835\n",
      "Epoch 1959/2000\n",
      "514/514 [==============================] - 0s 218us/step - loss: 0.4866 - acc: 0.7665 - val_loss: 0.4838 - val_acc: 0.7874\n",
      "Epoch 1960/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4954 - acc: 0.7840 - val_loss: 0.4816 - val_acc: 0.7756\n",
      "Epoch 1961/2000\n",
      "514/514 [==============================] - 0s 216us/step - loss: 0.4667 - acc: 0.7782 - val_loss: 0.4814 - val_acc: 0.7795\n",
      "Epoch 1962/2000\n",
      "514/514 [==============================] - 0s 212us/step - loss: 0.4861 - acc: 0.7646 - val_loss: 0.4826 - val_acc: 0.7835\n",
      "Epoch 1963/2000\n",
      "514/514 [==============================] - 0s 210us/step - loss: 0.4782 - acc: 0.7374 - val_loss: 0.4822 - val_acc: 0.7835\n",
      "Epoch 1964/2000\n",
      "514/514 [==============================] - 0s 208us/step - loss: 0.4834 - acc: 0.7763 - val_loss: 0.4823 - val_acc: 0.7874\n",
      "Epoch 1965/2000\n",
      "514/514 [==============================] - 0s 336us/step - loss: 0.4732 - acc: 0.7763 - val_loss: 0.4859 - val_acc: 0.7559\n",
      "Epoch 1966/2000\n",
      "514/514 [==============================] - 0s 260us/step - loss: 0.4820 - acc: 0.7626 - val_loss: 0.4834 - val_acc: 0.7756\n",
      "Epoch 1967/2000\n",
      "514/514 [==============================] - 0s 319us/step - loss: 0.4896 - acc: 0.7704 - val_loss: 0.4843 - val_acc: 0.7677\n",
      "Epoch 1968/2000\n",
      "514/514 [==============================] - 0s 287us/step - loss: 0.4737 - acc: 0.7724 - val_loss: 0.4897 - val_acc: 0.7559\n",
      "Epoch 1969/2000\n",
      "514/514 [==============================] - 0s 296us/step - loss: 0.5029 - acc: 0.7588 - val_loss: 0.4837 - val_acc: 0.7717\n",
      "Epoch 1970/2000\n",
      "514/514 [==============================] - 0s 276us/step - loss: 0.4746 - acc: 0.7724 - val_loss: 0.4874 - val_acc: 0.7677\n",
      "Epoch 1971/2000\n",
      "514/514 [==============================] - 0s 281us/step - loss: 0.4879 - acc: 0.7763 - val_loss: 0.4827 - val_acc: 0.7717\n",
      "Epoch 1972/2000\n",
      "514/514 [==============================] - 0s 284us/step - loss: 0.4772 - acc: 0.7821 - val_loss: 0.4820 - val_acc: 0.7835\n",
      "Epoch 1973/2000\n",
      "514/514 [==============================] - 0s 278us/step - loss: 0.4818 - acc: 0.7704 - val_loss: 0.4842 - val_acc: 0.7835\n",
      "Epoch 1974/2000\n",
      "514/514 [==============================] - 0s 298us/step - loss: 0.4788 - acc: 0.7665 - val_loss: 0.4887 - val_acc: 0.7480\n",
      "Epoch 1975/2000\n",
      "514/514 [==============================] - 0s 283us/step - loss: 0.4716 - acc: 0.7743 - val_loss: 0.4895 - val_acc: 0.7480\n",
      "Epoch 1976/2000\n",
      "514/514 [==============================] - 0s 251us/step - loss: 0.4663 - acc: 0.7704 - val_loss: 0.4901 - val_acc: 0.7520\n",
      "Epoch 1977/2000\n",
      "514/514 [==============================] - 0s 292us/step - loss: 0.4869 - acc: 0.7860 - val_loss: 0.4869 - val_acc: 0.7756\n",
      "Epoch 1978/2000\n",
      "514/514 [==============================] - 0s 295us/step - loss: 0.4732 - acc: 0.7607 - val_loss: 0.4843 - val_acc: 0.7717\n",
      "Epoch 1979/2000\n",
      "514/514 [==============================] - 0s 253us/step - loss: 0.5006 - acc: 0.7510 - val_loss: 0.4851 - val_acc: 0.7717\n",
      "Epoch 1980/2000\n",
      "514/514 [==============================] - 0s 247us/step - loss: 0.4866 - acc: 0.7763 - val_loss: 0.4868 - val_acc: 0.7756\n",
      "Epoch 1981/2000\n",
      "514/514 [==============================] - 0s 251us/step - loss: 0.4853 - acc: 0.7510 - val_loss: 0.4870 - val_acc: 0.7835\n",
      "Epoch 1982/2000\n",
      "514/514 [==============================] - 0s 230us/step - loss: 0.5096 - acc: 0.7471 - val_loss: 0.4846 - val_acc: 0.7874\n",
      "Epoch 1983/2000\n",
      "514/514 [==============================] - 0s 261us/step - loss: 0.4996 - acc: 0.7451 - val_loss: 0.4839 - val_acc: 0.7756\n",
      "Epoch 1984/2000\n",
      "514/514 [==============================] - 0s 270us/step - loss: 0.5026 - acc: 0.7451 - val_loss: 0.4849 - val_acc: 0.7756\n",
      "Epoch 1985/2000\n",
      "514/514 [==============================] - 0s 244us/step - loss: 0.4865 - acc: 0.7549 - val_loss: 0.4835 - val_acc: 0.7795\n",
      "Epoch 1986/2000\n",
      "514/514 [==============================] - 0s 251us/step - loss: 0.4890 - acc: 0.7704 - val_loss: 0.4811 - val_acc: 0.7717\n",
      "Epoch 1987/2000\n",
      "514/514 [==============================] - 0s 231us/step - loss: 0.5070 - acc: 0.7704 - val_loss: 0.4806 - val_acc: 0.7677\n",
      "Epoch 1988/2000\n",
      "514/514 [==============================] - 0s 231us/step - loss: 0.4700 - acc: 0.7996 - val_loss: 0.4823 - val_acc: 0.7717\n",
      "Epoch 1989/2000\n",
      "514/514 [==============================] - 0s 242us/step - loss: 0.4944 - acc: 0.7743 - val_loss: 0.4851 - val_acc: 0.7835\n",
      "Epoch 1990/2000\n",
      "514/514 [==============================] - 0s 250us/step - loss: 0.4950 - acc: 0.7588 - val_loss: 0.4864 - val_acc: 0.7756\n",
      "Epoch 1991/2000\n",
      "514/514 [==============================] - 0s 234us/step - loss: 0.4917 - acc: 0.7743 - val_loss: 0.4827 - val_acc: 0.7756\n",
      "Epoch 1992/2000\n",
      "514/514 [==============================] - 0s 253us/step - loss: 0.5032 - acc: 0.7588 - val_loss: 0.4837 - val_acc: 0.7756\n",
      "Epoch 1993/2000\n",
      "514/514 [==============================] - 0s 233us/step - loss: 0.4822 - acc: 0.7432 - val_loss: 0.4874 - val_acc: 0.7717\n",
      "Epoch 1994/2000\n",
      "514/514 [==============================] - 0s 241us/step - loss: 0.4718 - acc: 0.7588 - val_loss: 0.4854 - val_acc: 0.7795\n",
      "Epoch 1995/2000\n",
      "514/514 [==============================] - 0s 229us/step - loss: 0.4809 - acc: 0.7549 - val_loss: 0.4850 - val_acc: 0.7835\n",
      "Epoch 1996/2000\n",
      "514/514 [==============================] - 0s 230us/step - loss: 0.4948 - acc: 0.7646 - val_loss: 0.4842 - val_acc: 0.7756\n",
      "Epoch 1997/2000\n",
      "514/514 [==============================] - 0s 254us/step - loss: 0.4647 - acc: 0.7821 - val_loss: 0.4847 - val_acc: 0.7913\n",
      "Epoch 1998/2000\n",
      "514/514 [==============================] - 0s 288us/step - loss: 0.4919 - acc: 0.7607 - val_loss: 0.4826 - val_acc: 0.7717\n",
      "Epoch 1999/2000\n",
      "514/514 [==============================] - 0s 227us/step - loss: 0.4910 - acc: 0.7549 - val_loss: 0.4875 - val_acc: 0.7638\n",
      "Epoch 2000/2000\n",
      "514/514 [==============================] - 0s 214us/step - loss: 0.4846 - acc: 0.7588 - val_loss: 0.4861 - val_acc: 0.7835\n"
     ]
    }
   ],
   "source": [
    "H = model.fit(X_train, y_binary_train, validation_data=(X_test, y_binary_test),epochs = 2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['val_loss', 'val_acc', 'loss', 'acc'])"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "H.history.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a457e9908>]"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(H.history[\"loss\"])\n",
    "plt.plot(H.history[\"val_loss\"], 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x1a448c39b0>]"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(H.history[\"acc\"])\n",
    "plt.plot(H.history[\"val_acc\"], 'r')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(254,)"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_test.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred_softmax = model.predict(X_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = np.argmax(y_pred_softmax, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.83      0.84      0.84       167\n",
      "           1       0.69      0.67      0.68        87\n",
      "\n",
      "   micro avg       0.78      0.78      0.78       254\n",
      "   macro avg       0.76      0.76      0.76       254\n",
      "weighted avg       0.78      0.78      0.78       254\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report(y_test,y_pred))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python (spinningup)",
   "language": "python",
   "name": "spinningup"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
